Acm 2005

Computing Curricula 2005

The Overview Report
covering undergraduate degree programs in
Computer Engineering
Computer Science
Information Systems
Information Technology
Software Engineering

A volume of the Computing Curricula Series

The Joint Task Force for Computing Curricula 2005

A cooperative project of
The Association for Computing Machinery (ACM)
The Association for Information Systems (AIS)
The Computer Society (IEEE-CS)

30 September 2005

Computing Curricula 2005 – The Overview Report

Copyright © 2006 by ACM and IEEE.
All rights reserved.

Copyright and Reprint Permissions: Permission is granted to use these curriculum guidelines for the
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Sponsoring Societies
This report was made possible by
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ACM
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The Joint Task Force for
Computing Curricula 2005

Russell Shackelford is chair of the CC2005 Task Force. He is the previous chair of the ACM Education
Board. He has served as Associate Chair of the Computer Science Department at Stanford University
and as Director of Undergraduate Studies at Georgia Tech’s College of Computing. He was co-chair of
the CC2001 Task Force.

James H. Cross II is Philpott-Westpoint Stevens Professor and Chair of Computer Science and Software
Engineering at Auburn University. He is a past Vice President of the IEEE Computer Society’s
Educational Activities Board (EAB). He was a member of the CC2001 Task Force.

Gordon Davies recently retired after forty years of teaching, the last twenty of which were at the U.K.’s
Open University. In recent years, he helped create ACM’s Professional Development Center. He is now
actively involved in accreditation for the British Computer Society. He was a member of the CC2001 Task
Force.

John Impagliazzo is Professor of Computer Science at Hofstra University. He chaired the Accreditation
Committee of the ACM Education Board for twelve years. Currently, he is editor-in-chief of Inroads - The
SIGCSE Bulletin, chair of the IFIP Working Group 9.7 on the History of Computing, and an active member
and treasurer of the IEEE History Committee. He was a member of the CE2004 Task Force.

Reza Kamali is an Associate Professor and Department Head of Computer Information Systems and
Information Technology at Purdue University Calumet, Hammond, Indiana. He was a founding member of
SITE, which later became ACM’s SIGITE. He now serves as SIGITE Education Officer. He is a member
of the IT2006 Task Force.

Richard LeBlanc recently retired as Professor of Computer Science, College of Computing, Georgia
Tech. He now serves as Vice President for Academic Affairs, Southern Catholic College. He is a past
Chair and Vice Chair of the ACM Education Board, a member of IFIP Working Group 3.2 (Informatics
Education at the University Level), a Team Chair for ABET’s Computing Accreditation Commission, and a
Software Engineering Program Evaluator for the Engineering Accreditation Commission. He was co-chair
of the SE2004 Task Force.

Barry Lunt is Associate Professor of Information Technology at Brigham Young University. He was a
founding member of SITE, which later became ACM’s SIGITE. He is a member of the IEEE Computer
Society, the IEEE Communication Society, and ASEE. He is chair of the IT2006 Task Force.

Andrew McGettrick is Professor of the Department of Computer and Information Sciences, University of
Strathclyde, Glasgow, Co-chair of the ACM Education Board, and a Vice President of the British
Computer Society. He recently chaired groups that created benchmark standards for undergraduate and
Masters degree programs in Computing in the U.K. He was a member of the CC2001 Task Force, the
CE2004 Task Force, and the SE2004 Task Force.

Robert Sloan is Associate Professor in the Computer Science Department of the University of Illinois at
Chicago. He is an active member of the Educational Activities Board of the IEEE Computer Society.
He was a member of the CC2001 Task Force and the CE2004 Task Force

Heikki Topi is Associate Professor of Computer Information Systems and Chair of the CIS Department at
Bentley College, Waltham, MA. He is active in the Association for Information Systems (AIS) and is
involved in curriculum development and accreditation activities within the North American IS community.
He was a member of the IS2002 Task Force.

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Page iv


Table of Contents
Sponsoring societies and copyright notice................................................................................... ii
Members of the CC2005 Task Force ........................................................................................... iii
Table of Contents ......................................................................................................................... v

Summary ..................................................................................................................................... 1
1. Introduction........................................................................................................................... 3
1.1. Purpose ...................................................................................................................... 3
1.2. Scope .......................................................................................................................... 3
1.3. Background and history ............................................................................................. 5
1.4. Guiding principles ..................................................................................................... 7

2. The Computing Disciplines .................................................................................................. 9
2.1. What is computing? .................................................................................................... 9
2.2. The landscape of the computing disciplines ............................................................... 9
2.2.1. Before the 1990s.............................................................................................. 9
2.2.2. Significant developments of the 1990s ...........................................................10
2.2.3. After the 1990s ................................................................................................12
2.3. Descriptions of the computing disciplines..................................................................13
2.3.1. Computer engineering .....................................................................................13
2.3.2. Computer science ............................................................................................13
2.3.3. Information systems ........................................................................................14
2.3.4. Information technology ...................................................................................14
2.3.5. Software engineering.......................................................................................15
2.4. Graphical views of the computing disciplines............................................................15

3. Degree programs and expectations of graduates ...................................................................23
3.1. Curriculum summaries: A tabular comparison of computing degree programs.........23
3.1.1. What the tabular view represents ....................................................................24
3.1.2. Using the table: two related examples.............................................................26
3.2. Degree outcomes: Comparing expectations of degree program graduates.................27
3.3. International Differences ............................................................................................29
3.4. The pace of change in academia: The disciplines and the available degrees .............29
3.5. The pace of change in the workplace: The degrees and career opportunities ............35
3.6. A shared identity: The common requirements of a computing degree.......................35

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4. Institutional considerations....................................................................................................37
4.1. Evolution of computing degree programs ..................................................................37
4.2. The portfolio strategy .................................................................................................38
4.3. Institutional challenges to diversity ............................................................................40
4.3.1. Faculty development and adaptation...............................................................40
4.3.2. Organizational structure ..................................................................................41
4.3.3. Curricular structure .........................................................................................41
4.4. Academic integrity and market forces ........................................................................44
4.5. Computing curricula and accreditation.......................................................................45
4.5.1. Benefits of discipline-specific accreditation ...................................................45
4.5.2. Accreditation and quality ................................................................................46
4.5.3. National; traits and international cooperation .................................................47
4.5.4. Accreditation in the U.K. ................................................................................48
4.5.5. Accreditation in the U.S. .................................................................................48
5. Next steps ..............................................................................................................................49

References .................................................................................................................................51

Glossary .......................................................................................................................................52

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Summary
Computing has dramatically influenced progress in science, engineering, business, and many other areas
of human endeavor. In today’s world, nearly everyone needs to use computers, and many will want to
study computing in some form. Computing will continue to present challenging career opportunities, and
those who work in computing will have a crucial role in shaping the future.
It is important that the computing disciplines attract quality students from a broad cross section of the
population and prepare them to be capable and responsible professionals, scientists, and engineers. Over
the years, professional and scientific computing societies based in the U.S. have taken a leading role in
providing support for higher education in various ways, including the formulation of curriculum
guidelines. Several reports that define and update guidelines for computing curricula have appeared over
the past four decades. Recent efforts have targeted international participation, reflecting the need for the
leading professional organizations to become truly global in scope and responsibility.
Early in the process that produced Computing Curricula 2001 (CC2001), it became clear that the dramatic
expansion of computing during the 1990s made it no longer reasonable to produce updated curriculum
reports just for the disciplines for which reports existed previously. CC2001 called for a set of reports to
cover the growing family of computing-related disciplines, including a separate volume for computer
science, information systems, computer engineering, and software engineering. It was also clear that
new computing disciplines would emerge over time. Since the publication of CC2001, information
technology has joined the family of computing disciplines and now requires its own curriculum volume.
The CC2001 report also called for an Overview Report to summarize the content of the various discipline-
specific reports. This document is the first edition of that Overview Report. Its goal is to provide
perspective for those in academia who need to understand what the major computing disciplines are and
how the respective undergraduate degree programs compare and complement each other. This report
summarizes the body of knowledge for undergraduate programs in each of the major computing
disciplines, highlights their commonalities and differences, and describes the performance characteristics
of graduates from each kind of undergraduate degree program. To create this report, we have examined
curriculum guidelines for undergraduate education and have referred to the computing professions and
other supporting information as necessary. We have not focused on graduate education or on the identities
of the computing research communities. College-level faculty and administrators are the audience for this
report. It outlines the issues and challenges they will face in shaping the undergraduate programs that will
serve their constituents and their communities.
Following the publication of the Overview Report, the Joint Task Force will publish a shorter companion
report, The Guide to Undergraduate Programs in Computing. The Guide will offer guidance to a broader
audience, including prospective students, their parents and guidance counselors, and others who have
reason to care about the choices that await students who move from high school to college. It will
provide brief characterizations of the computing disciplines, profile factors that students might consider
when choosing an area of computing study, and it will be widely distributed as an independent document.
This report is the result of an unprecedented cooperative effort among the leading computer societies and
the major computing disciplines. It is based on inspection and analysis of the five discipline-specific
volumes of the Computing Curricula Series. Because most of these documents are oriented to higher
education in the United States and Canada, this report is implicitly North American-centric. We expect
future generations of all such volumes to be more international in scope. Until then, this report provides
context that may help those in other nations know how to best use these reports in their current context.
Because things change rapidly in computing, the reports will require frequent updates. Electronic copies
of the most recent edition of this and other computing curricula reports can be found at
http://www.acm.org/education/curricula.html and at http://computer.org/curriculum.

Page 1



Page 2


Chapter 1: Introduction
1.1. Purpose of This Report
This report provides an overview of the different kinds of undergraduate degree programs in computing
that are currently available and for which curriculum standards are now, or will soon be, available.
Teachers, administrators, students, and parents need this report because computing is a broad discipline
that crosses the boundaries between mathematics, science, engineering, and business and because
computing embraces important competencies that lie at the foundation of professional practice.
Computing consists of several fields, and many respected colleges and universities offer undergraduate
degree programs in several of them such as computer science, computer engineering, information
systems, information technology, software engineering, and more. These computing fields are related but
also quite different from each other. The variety of degree programs in computing presents students,
educators, administrators, and other community leaders with choices about where to focus their efforts.
Several questions naturally arise. What are these different kinds of computing degree programs? How
are they similar? How do they differ? How can I tell what their names really mean? Which kinds of
programs should our local college or university offer? And so on. These are all valid questions, but to
anyone unfamiliar with the breadth of computing, the responses to these queries may be difficult to
articulate. This report may help to provide some answers.
We have created this report to explain the character of the various undergraduate degree programs in
computing and to help you determine which of the programs are most suited to particular goals and
circumstances. We intend this report to serve a broad and varied audience. We think it can be helpful to:
• university faculty and administrators who are developing plans and curricula for computing-related
programs at their institutions, and to those who guide the accreditation of such programs, and
• responsible parties in public education, including boards of education, government officials, elected
representatives, and others who seek to represent the public interest.
In addition, we will soon be preparing The Guide to Undergraduate Degree Programs in Computing
(henceforth the Guide). The Guide will be an independent companion document that will be broadly
distributed to a more general audience. It is intended to serve:
• students who are trying to determine which path of computing study fits their interests and goals,
• parents, teachers, guidance counselors, and others who are trying to assist students in their choices,
• professionals considering how to continue their education in a rapidly changing, dynamic field, and
• anyone who is trying to make sense of the wide range of undergraduate degree programs in computing
that are now available.

1.2. Scope of This Report
There are many kinds of computing degree programs. Reliable information about the number of different
kinds of computing degree programs is hard to come by, but over the last ten years or so, there has been a
dramatic increase in the number and type of computing degree programs available to students. It is
beyond both our goal and our capability to catalog and characterize them all. In this report, we focus on
five that are prominent today: computer engineering (CE), computer science (CS), information systems
(IS), information technology (IT), and software engineering (SE). These five satisfy our criterion for
inclusion, that is, each one has, or will soon have, a recent volume of undergraduate curriculum guidelines

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that is approved and published by one or more international professional and scientific societies. These
five also attract the overwhelming majority of all U.S. undergraduates who are majoring in computing.
We expect that, in the future, additional disciplines in computing may satisfy our criterion. When that is
the case, they may be included in future editions of this report. Candidates for future editions might
include new fields that don’t yet have such guidelines (e.g., bioinformatics) and more established fields
that have not recently issued such guidelines (e.g., computer engineering technology).
The foundation of this report is the set of curriculum standards that exist for undergraduate degree
programs in the five major computing-related fields mentioned above. Each one of the five discipline-
specific curricula volumes represents the best judgment of the relevant professional, scientific, and
educational associations and serves as a definition of what these degree programs should be and do.
While some of these reports may be scheduled for revision, we have made no effort to update their
contents as that is beyond our mission and authority. Rather, we have taken what is given in the five
current curricula volumes, compared their contents to one another, and synthesized what we believe to be
essential descriptive and comparative information. The five curricula volumes contain a great deal of
detailed information not included here. Readers who want detailed information about any of the five
disciplines covered in this report should consult the original sources. The computing curricula volumes
can be found at http://www.acm.org/education/curricula.html and http://computer.org/curriculum.
In addition to using these five reports as the basis for this report, we have referred to the computing
professions and other supporting information as necessary. We have not focused on other kinds of
undergraduate computing degree programs, on graduate education in computing, or on the identities of
the computing research communities. Nor have we included any information or comment about non-
traditional computing education such as provided in conjunction with vendor-specific certification
programs; those arenas are deserving of evaluation, but such work is beyond the scope of this project.
The remainder of this report includes the following,
• In Chapter 2, we characterize each of the five major disciplines of computing.
• In Chapter 3, we flesh out the characteristics of each of these five kinds of degree program and
compare them to each other. We also compare and contrast the kind of professional capabilities
expected of the graduates of each kind of degree program.
• In Chapter 4, we conclude by alerting educators, administrators, and other responsible parties to some
issues that may emerge in the creation of new fields of computing.
• In Chapter 5, we tell you how to obtain online copies of the five discipline-specific curriculum reports
and offer guidance about how to use them.
Following publication of this report, we will prepare and publish a Guide to Undergraduate Programs in
Computing. This will be a shorter stand-alone document to be distributed more widely than the Overview
Report. In it, we will provide information for prospective students, and for those who advise them, to
help them make well-informed choices.
Computing itself will continue to evolve. In addition, new computing-related fields are likely to emerge.
As we update the existing discipline-specific reports and, as additional reports for new fields of
computing emerge, you can expect to see updated versions of this report. To find out if this document
(CC2005-Overview) is the most recent edition of the Overview Report on Computing Curricula, go to
http://www/education/curricula.html or http://computer.org/curriculum. From either of these sites, you
will be able to determine if a newer version exists. If a newer version exists, you may download the
newest version from either site.

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1.3. Background and History
Over the last forty years, four major organizations in the U.S. have developed computing curriculum
guidelines for colleges and universities:
• The Association for Computing Machinery (generally called ACM or the Association for Computing)
is a scientific and professional organization founded in 1947. It is concerned with the development and
sharing of new knowledge about all aspects of computing (the word machinery in its name is a
historical artifact). It has traditionally been the professional home of computer scientists who devise
new ways of using computers and who advance the science and theory that underlies both computation
itself and the software that enables it. ACM began publishing curriculum recommendations for CS in
1968 (a preliminary version appeared in 1965) and for IS in 1972.
• The Association for Information Systems (generally called “AIS”) was founded in 1994. It is a global
organization serving academics who specialize in Information Systems. Most academic members of
AIS are affiliated with Schools/Colleges of Business or Management. AIS began providing curriculum
recommendations for IS in cooperation with ACM and AITP in 1997.
• The Association for Information Technology Professionals (often referred to as AITP) was founded in
1951 as the National Machine Accountants Association. In 1962, it became the Data Processing
Management Association (or DPMA). It adopted its present name in 1996. AITP focuses on the
professional side of computing, serving those who use computing technology to meet the needs of
business and other organizations. It first provided curriculum recommendations for IS in 1985.
• The Computer Society of the Institute for Electrical and Electronic Engineers (often referred to as
IEEE-CS or the Computer Society) originated in 1946 as the committee on Large Scale Computing
Devices of the American Institute of Electrical Engineers (AIEE) and, in 1951, as the Professional
Group on Electronic Computers of the Institute of Radio Engineers (IRE). The AIEE and the IRE
merged in 1964 to become the IEEE, and the two subunits joined to become the Computer Society. The
Computer Society is a technical society within the IEEE that is focused on computing from the
engineering perspective. Today the Computer Society's members include computer engineers, software
engineers, computer technologists, and computer scientists. It began providing curriculum
recommendations in 1977. In recent years, there has been a large overlap in membership between
ACM and the Computer Society.
Prior to the 1990s, each society produced its own curriculum recommendations. Over time, the
advantages of cooperative work among them became obvious. Today, the societies cooperate in creating
curriculum standards, and, in this way, send a single message to the computing community. Many
researchers and teachers belong to more than one of the societies.
ACM and IEEE-CS joined forces in the late 1980s to create a joint curriculum report for computing.
Published in 1991 and known as Computing Curricula 1991 or CC’91 [CC91], it provided guidelines for
curricula for four-year Bachelor’s degree programs in computer science and computer engineering.
Throughout the 1990s, various efforts were made to produce curricula guidelines for other programs in
computing education. By 1993, ACM had produced five reports for two-year Associate degree programs,
one report each for computer science, computer engineering technology, information systems, computer
support services, and computing for other disciplines. [AssocDeg] Also in 1993, ACM produced
curriculum recommendations for a high school curriculum [HS]. In 1997, ACM, AIS, and AITP [AIS]
published a model curriculum and a set of guidelines for four-year Bachelors degree programs in
information systems [IS97]. The 1990s also saw newer computing fields such as software engineering
gain increased prominence in the U.S.
By the end of the 1990s, it was becoming clear that the field of computing had not only grown rapidly but
had also grown in many dimensions. The proliferation of different kinds of degree programs in

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computing left many people confused. Given the growing number of kinds of computing degree
programs, confusion was perhaps inevitable. This diversity of computing degrees was a problem that had
not existed in a significant way prior to the explosion of computing’s impact in the 1990s. Because it was
a new problem, there was no established way of coordinating and simplifying the choices that suddenly
seemed to be appearing everywhere.
When ACM and IEEE-CS again joined forces in the late 1990s to produce an up-to-date curriculum
report to replace CC’91, these organizations could no longer ignore the problem. The original plan called
for the two societies to form a joint task force that would update the CC’91 report. ACM and IEEE-CS
created a joint task force and its goal was to produce Computing Curricula 2001 [CC2001], a single report
that would provide curriculum guidelines for degree programs for the various computing disciplines.
However, the members of the task force soon recognized the new reality: computing had grown in so
many dimensions that no single view of the field seemed adequate. The days when the field of computing
consisted of only computer science, computer engineering and information systems were over, and the
richness and breadth provided by the various computing disciplines called for a new way of defining what
computing curricula should be.
The CC2001 Task Force faced this challenge by making four important decisions.
1. There should be a curriculum report (or volume) for each of the major computing disciplines,
including computer engineering, computer science, information systems, and software engineering.
2. The number of computing-related disciplines is likely to grow. The curriculum report structure must
accommodate not only the four computing disciplines that were established at that time (enumerated
above) but also new computing disciplines as they emerge.
3. The growing number of computing disciplines naturally causes confusion. Therefore, in addition to
the various discipline-specific volumes, there must also be an Overview report to serve as a practical
umbrella guide to the discipline-specific volumes.
4. The pace of change in computing is sufficiently rapid that a process must be established for the
organizations to update curriculum guidelines more frequently than once per decade.
The Task Force recognized that its members were primarily computer scientists and deemed itself
qualified to produce a report only for computer science. It called for ACM, IEEE-CS, AIS, and other
professional societies to undertake a cooperative effort to create the volumes for computer engineering,
information systems, and software engineering. The work of this task force, known as Computing
Curricula 2001 (CC2001), was published in December 2001 [CC2001]. The CC2001 Report contains
two important components:
• a new structure for computing curriculum guidelines encompassing the decisions taken by the Task
Force described above and henceforth referred to as the CC2001 model, and
• detailed curricula guidelines for undergraduate degree programs in computer science.
Because the CC2001 report included CS curriculum guidelines, those who refer to it for its computer
science content might think of as CS2001. Beginning with the publication of the CC2005 report, the title
“Computing Curricula 20xx” will be used for Overview reports. New editions of the CS curriculum
guidelines will be called “Computer Science 20xx”. In all cases, “20xx” will be the year of publication.
In response to the CC2001 model, work soon began on other discipline-specific volumes:
• The information systems community published its updated IS2002 report in 2002 [IS2002].
• The software engineering community published its first report, SE2004, in 2004 [SE2004].

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• The computer engineering community published its CE2004 report in 2004 [CE2004].
• The CC2001 prediction of additional emerging computing disciplines has already proved correct. A
report on degree programs in information technology is under development. We anticipate that it will
be published in 2006 and thus refer to it as IT2006.
The diagram in Figure 1.1 represents the scope of what has become the Computing Curricula Series, a
continuing effort to provide guidelines and standards for computing curricula. The top-level Overview
block, CC2005, represents this report. Each of the first five sub-blocks represents a curriculum report for
one of the existing computing disciplines. The sixth sub-block is a placeholder for future reports on
additional computing disciplines as necessitated by the emergence of new computing disciplines. Online
copies of the computing curricula volumes can be found at http://www.acm.org/education/curricula.html
and http://computer.org/curriculum.

CC2005
The Overview
Volume
on
Undergraduate
Degree
Programs
in Computing

CC2001 IS2002 SE2004 CE2004 IT2006 Other
(CS2001) curriculum
Computer Information Software Computer Information volumes as
Science Systems Engineering Engineering Technology needed for
Curriculum Curriculum Curriculum Curriculum Curriculum emerging
Volume Volume Volume Volume Volume disciplines

Figure 1.1. Structure of the Computing Curricula Series

1.4. Guiding Principles
Five principles guided the development of this report.
1. The dramatic growth in the number of computing disciplines and their collective impact on society
requires that the computing disciplines articulate a shared identity. Given the importance of
computing to society, we in computing have a responsibility to help society understand what we do.
The fact that computing offers several kinds of academic programs is a major strength and an
opportunity but requires that we offer society a practical vision of our shared field, of the various
disciplines within it, and of the meaningful choices that face students, educators, and their
communities. The goal of this report is to articulate the shared identity, the separate identities of each
computing discipline, and the choices available to students, educators, and communities.

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2. Each computing discipline must be a participant in defining the identities and choices as
articulated in this report. Each computing discipline must articulate its own identity, recognize the
identities of the other disciplines, and contribute to the shared identity of computing.
3. This report must address a broad audience, not just its technically oriented constituents. As
discussed in Section 1.1, the audience for this report includes a range of people who have reason to
become familiar with academic computing degree programs. Most members of that audience are not
computing educators. Our goal is to paint a concise and useful picture that will illuminate the choices
faced by students and by those who are responsible for shaping their educational choices. This goal is
fundamentally different from the goal of reports that define curriculum guidelines for degree
programs. It dictates that we must be relatively concise and that we minimize technical jargon. We
ask the technically oriented reader to appreciate our need to avoid the kind of distinctions and
technical emphasis expected of documents aimed at a technical audience.
4. We should characterize the computing disciplines at the undergraduate level by reference to the
body of knowledge and skills defined in the most recent curriculum report for each of these
disciplines. The definition of a shared characterization of the computing disciplines is
unprecedented, and it is imperative that we set attainable goals. We confine our attention to the
bodies of knowledge and skills defined by each computing discipline as published in the individual
curriculum reports; we do not consider pedagogy or course definition. We believe that pedagogical
issues and the definition of computing courses that might serve multiple audiences across the
computing disciplines are important and timely concerns. However, we believe we would be ill
advised to address such issues in this report. This decision should not be construed as a precedent for
others to follow, and we expect that authors of subsequent reports will revisit this issue.
5. This report must go beyond an examination of details to generate a useful synthesis for the
intended audience. While the findings of this report are based on examination of the bodies of
knowledge in current discipline-specific curriculum volumes, we must go beyond simple examination
and reporting to generate a synthesis that will be meaningful and useful for our audience. Our task
requires representatives of each discipline to make judgments about how to form an insightful,
consensus-based overview of the computing disciplines.

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Chapter 2. The Computing Disciplines
There are many kinds of computing degree programs. There are dozens around the world. The variety of
names used for the programs is even broader. The programs represent a number of computing disciplines.
In this report, we focus on five that are prominent today: computer engineering, computer science,
information systems, information technology, and software engineering. These five satisfy our criterion
for inclusion: each one has, or will soon have, a volume of undergraduate curriculum guidelines that is
approved and published by one or more international professional and scientific societies. We expect
that, in the future, additional computing disciplines may satisfy this criterion. When that is the case, they
may be included in future editions of this report.

2.1. What Is Computing?
In a general way, we can define computing to mean any goal-oriented activity requiring, benefiting from,
or creating computers. Thus, computing includes designing and building hardware and software systems
for a wide range of purposes; processing, structuring, and managing various kinds of information; doing
scientific studies using computers; making computer systems behave intelligently; creating and using
communications and entertainment media; finding and gathering information relevant to any particular
purpose, and so on. The list is virtually endless, and the possibilities are vast. Computing also has other
meanings that are more specific, based on the context in which the term is used. For example, an
information systems specialist will view computing somewhat differently from a software engineer.
Regardless of the context, doing computing well can be complicated and difficult. Because society needs
people to do computing well, we must think of computing not only as a profession but also as a discipline.
A student typically earns a bachelors degree in one of the computing disciplines to prepare for entry into
the computing profession. Because computing provides such a wide range of choices, it is impossible for
anyone to become proficient at all of them. Hence, an individual who wishes to become a computing
professional requires some focus for his or her professional life. There are currently five major kinds of
undergraduate degree programs in computing, and each one provides a different focus and perspective on
the discipline of computing. In the next section, we shall see what these five computing disciplines are
and how they compare in terms of their focus and the kinds of problems and issues they address.

2.2. The Landscape of Computing Disciplines
Computing is not just a single discipline but is a family of disciplines. During the 1990s, important
changes in computing and communications technology and in the impact of that technology on society led
to important changes in this family of disciplines.
2.2.1. Before the 1990s
Undergraduate degree programs in the computing-related disciplines began to emerge in the 1960s.
Originally, there were only three kinds of computing-related degree programs in North America:
computer science, electrical engineering, and information systems. Each of these disciplines was
concerned with its own well-defined area of computing. Because they were the only prominent
computing disciplines and because each one had its own area of work and influence, it was much easier
for students to determine which kind of degree program to choose. For students who wanted to become
expert in developing software or with the theoretical aspects of computing, computer science was the
obvious choice. For students who wanted to work with hardware, electrical engineering was the clear
option. For students who wanted to use hardware and software to solve business problems, information
systems was the right choice.

Page 9


Each of these three disciplines had its own domain. There was not any shared sense that they constituted
a family of computing disciplines. As a practical matter, computer scientists and electrical engineers
sometimes worked closely together since they were both concerned with developing new technology,
were often housed in the same part of the university, and sometimes required each others’ help.
Information systems specialists had ties with business schools and did not have much interaction with
computer scientists and electrical engineers.
Before the 1990s, the only major change in this landscape in the U.S. was the development of computer
engineering. Prior to the invention of chip-based microprocessors, computer engineering was one of
several areas of specialization within electrical engineering. With the advent of the microprocessor in the
mid-1970s, computer engineering began to emerge from within electrical engineering to become a
discipline unto itself. For many people outside of the engineering community, however, the distinction
between electrical engineering and computer engineering was not clear. Before the 1990s, therefore,
when prospective students surveyed the choices of computing-related degree programs, most would have
perceived the computing disciplines as shown in the top half of Figure 2.1. The distance between the
disciplines indicates how closely the people in those disciplines worked with each other.
2.2.2. Significant Developments of the 1990s
During the 1990s, several developments changed the landscape of the computing disciplines in North
America, although in other parts of the world some of these changes occurred earlier.
• Computer engineering solidified its emergence from electrical engineering. Computer engineering
emerged from electrical engineering during the late 1970s and the 1980s, but it was not until the 1990s
that computer chips became basic components of most kinds of electrical devices and many kinds of
mechanical devices. (For example, modern automobiles contain numerous computers that perform
tasks that are transparent to the driver.) Computer engineers design and program the chips that permit
digital control of many kinds of devices. The dramatic expansion in the kinds of devices that rely on
chip-based digital logic helped computer engineering solidify its status as a strong field and, during the
1990s, unprecedented numbers of students applied to computer engineering programs. Outside of
North America, these programs often had titles such as computer systems engineering.
• Computer science grew rapidly and became accepted into the family of academic disciplines. At most
American colleges and universities, computer science first appeared as a discipline in the 1970s.
Initially, there was considerable controversy about whether computer science was a legitimate
academic discipline. Proponents asserted that it was a legitimate discipline with its own identity, while
critics dismissed it as a vocational specialty for technicians, a research platform for mathematicians, or
a pseudo-discipline for computer programmers. By the 1990s, computer science had developed a
considerable body of research, knowledge, and innovation that spanned the range from theory to
practice, and the controversy about its legitimacy died. Also during the 1990s, computer science
departments faced unprecedented demands. Industry needs for qualified computer science graduates
exceeded supply by a large factor. Enrollments in CS programs grew very dramatically. While CS had
already experienced cycles of increasing and decreasing enrollments throughout its brief history, the
enrollment boom of the 90s was of such magnitude that it seriously stressed the ability of CS
departments to handle the very large numbers of students. With increased demands for both teaching
and research, the number of CS faculty at many universities grew significantly.
• Software engineering had emerged as an area within computer science. As computing is used to attack
a wider range of complex problems, creating reliable software becomes more difficult. With large,
complex programs, no one person can understand the entire program, and various parts of the program
can interact in unpredictable ways. (For example, fixing a bug in one part of a program can create new
bugs elsewhere.) Computing is also used in safety-critical tasks where a single bug can cause injury or
death. Over time, it became clear that producing good software is very difficult, very expensive, and

Page 10


very necessary. This lead to the creation of software engineering, a term that emanated from a NATO
sponsored conference held in Garmisch, Germany in 1968. While computer science (like other
sciences) focuses on creating new knowledge, software engineering (like other engineering disciplines)
focuses on rigorous methods for designing and building things that reliably do what they’re supposed
to do. Major conferences on software engineering were held in the 1970s and, during the 1980s, some
computer science degree programs included software engineering courses. However, in the U.S. it was
not until the 1990s that one could reasonably expect to find software engineering as a significant
component of computer science study at many institutions.
• Software engineering began to develop as a discipline unto itself. Originally the term software
engineering was introduced to reflect the application of traditional ideas from engineering to the
problems of building software. As software engineering matured, the scope of its challenge became
clearer. In addition to its computer science foundations, software engineering also involves human
processes that, by their nature, are harder to formalize than are the logical abstractions of computer
science. Experience with software engineering courses within computer science curricula showed
many that such courses can teach students about the field of software engineering but usually do not
succeed at teaching them how to be software engineers. Many experts concluded that the latter goal
requires a range of coursework and applied project experience that goes beyond what can be added to a
computer science curriculum. Degree programs in software engineering emerged in the United
Kingdom and Australia during the 1980s, but these programs were in the vanguard. In the United
States, degree programs in software engineering, designed to provide a more thorough foundation than
can be provided within computer science curricula, began to emerge during the 1990s.
• Information systems had to address a growing sphere of challenges. Prior to the 1990s, many
information systems specialists focused primarily on the computing needs that the business world had
faced since the 1960s: accounting systems, payroll systems, inventory systems, etc. By the end of the
1990’s, networked personal computers had become basic commodities. Computers were no longer
tools only for technical specialists; they became integral parts of the work environment used by people
at all levels of the organization. Because of the expanded role of computers, organizations had more
information available than ever before and organizational processes were increasingly enabled by
computing technology. The problems of managing information became extremely complex, and the
challenges of making proper use of information and technology to support organizational efficiency
and effectiveness became crucial issues. Because of these factors, the challenges faced by information
systems specialists grew in size, complexity, and importance. In addition, information systems as a
field paid increasing attention to the use of computing technology as a means for communication and
collaborative decision making in organizations.
• Information technology programs began to emerge in the late 1990s. During the 1990s, computers
became essential work tools at every level of most organizations, and networked computer systems
became the information backbone of organizations. While this improved productivity, it also created
new workplace dependencies as problems in the computing infrastructure can limit employees’ ability
to do their work. IT departments within corporations and other organizations took on the new job of
ensuring that the organization’s computing infrastructure was suitable, that it worked reliably, and that
people in the organization had their computing-related needs met, problems solved, etc. By the end of
the 1990s, it became clear that academic degree programs were not producing graduates who had the
right mix of knowledge and skills to meet these essential needs. College and universities developed
degree programs in information technology to fill this crucial void.
Collectively these developments reshaped the landscape of the computing disciplines. Tremendous
resources were allocated to information technology activities in all industrialized societies because of
various factors, including the explosive growth of the World Wide Web, anticipated Y2K problems, and
in Europe, the launch of the Euro.

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2.2.3. After the 1990s
The new landscape of computing degree programs reflects the ways in which computing as a whole has
matured to address the problems of the new millennium. In the U.S., computer engineering had solidified
its status as a discipline distinct from electrical engineering and assumed a primary role with respect to
computer hardware and related software. Software engineering has emerged to address the important
challenges inherent in building software systems that are reliable and affordable. Information technology
has come out of nowhere to fill a void that the other computing disciplines did not adequately address.
This maturation and evolution has created a greater range of possibilities for students and educational
institutions. The increased diversity of computing programs means that students face choices that are
more ambiguous than they were before the 1990s. The bottom portion of Figure 2.1 shows how
prospective students might perceive the current range of choices available to them. The dotted ovals
show how prospective students are likely to perceive the primary focus of each discipline.
It is clear where students who want to study hardware should go. Computer engineering has emerged
from electrical engineering as the home for those working on the hardware and software issues involved
in the design of digital devices. For those with other interests, the choices are not so clear-cut. In the pre-
1990s world, students who wanted to become expert in software development would study computer
science. The post-1990s world presents meaningful choices: computer science, software engineering, and
even computer engineering each include their own perspective on software development. These three
choices imply real differences: for CE, software attention is focused on hardware devices; for SE, the
emphasis is on creating software that satisfies robust real-world requirements; and for CS, software is the
currency in which ideas are expressed and a wide range of computing problems and applications are

Pre-1990s:

EE+
CE
CS IS
HARDWARE SOFTWARE BUSINESS

Post-1990s:

EE CE CS SE IT IS

HARDWARE SOFTWARE ORGANIZATIONAL
NEEDS

Figure 2.1. Harder Choices: How the Disciplines Might Appear to Prospective Students
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explored. Such distinctions may not be visible to prospective students. Naïve students might perceive
that all three disciplines share an emphasis on software and are otherwise indistinguishable.
Similarly, in the pre-1990s world, a primary area for applying computing to solve real-world problems
was in business, and information systems was the home for such work. The scope of real-world uses has
broadened from business to organizations of every kind, and students can choose between information
systems and information technology programs. While the IT and IS disciplines both include a focus on
software and hardware, neither discipline emphasizes them for their own sake; rather, they use technology
as critical instruments for addressing organizational needs. While IS focuses on the generation and use of
information, and IT focuses on ensuring that the organization’s infrastructure is appropriate and reliable,
prospective students might be unaware of these important differences and see only that IS and IT share a
purpose in using computing to meet the needs of technology-dependent organizations.

2.3. Descriptions of the Major Computing Disciplines
In this section, we characterize each of the five major computing disciplines. See Sections 3.4 and 3.5 for
more information on how to understand this important distinction between the names of the computing
disciplines and the names of a particular degree program.
2.3.1. Computer Engineering
Computer engineering is concerned with the design and construction of computers and computer-based
systems. It involves the study of hardware, software, communications, and the interaction among them.
Its curriculum focuses on the theories, principles, and practices of traditional electrical engineering and
mathematics and applies them to the problems of designing computers and computer-based devices.
Computer engineering students study the design of digital hardware systems including communications
systems, computers, and devices that contain computers. They study software development, focusing on
software for digital devices and their interfaces with users and other devices. CE study may emphasize
hardware more than software or there may be a balanced emphasis. CE has a strong engineering flavor.
Currently, a dominant area within computing engineering is embedded systems, the development of
devices that have software and hardware embedded in them. For example, devices such as cell phones,
digital audio players, digital video recorders, alarm systems, x-ray machines, and laser surgical tools all
require integration of hardware and embedded software and all are the result of computer engineering.

2.3.2. Computer Science
Computer science spans a wide range, from its theoretical and algorithmic foundations to cutting-edge
developments in robotics, computer vision, intelligent systems, bioinformatics, and other exciting areas.
We can think of the work of computer scientists as falling into three categories.
• They design and implement software. Computer scientists take on challenging programming jobs.
They also supervise other programmers, keeping them aware of new approaches.
• They devise new ways to use computers. Progress in the CS areas of networking, database, and
human-computer-interface enabled the development of the World Wide Web. Now CS researchers are
working with scientists from other fields to make robots become practical and intelligent aides, to use
databases to create new knowledge, and to use computers to help decipher the secrets of our DNA.
• They develop effective ways to solve computing problems. For example, computer scientists develop
the best possible ways to store information in databases, send data over networks, and display complex
images. Their theoretical background allows them to determine the best performance possible, and their
study of algorithms helps them to develop new approaches that provide better performance.

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Computer science spans the range from theory through programming. Curricula that reflect this breadth
are sometimes criticized for failing to prepare graduates for specific jobs. While other disciplines may
produce graduates with more immediately relevant job-related skills, computer science offers a
comprehensive foundation that permits graduates to adapt to new technologies and new ideas.
2.3.3. Information Systems
Information systems specialists focus on integrating information technology solutions and business
processes to meet the information needs of businesses and other enterprises, enabling them to achieve
their objectives in an effective, efficient way. This discipline’s perspective on information technology
emphasizes information, and views technology as an instrument for generating, processing, and
distributing information. Professionals in the discipline are primarily concerned with the information that
computer systems can provide to aid an enterprise in defining and achieving its goals, and the processes
that an enterprise can implement or improve using information technology. They must understand both
technical and organizational factors, and they must be able to help an organization determine how
information and technology-enabled business processes can provide a competitive advantage.
The information systems specialist plays a key role in determining the requirements for an organization’s
information systems and is active in their specification, design, and implementation. As a result, such
professionals require a sound understanding of organizational principles and practices so that they can
serve as an effective bridge between the technical and management communities within an organization,
enabling them to work in harmony to ensure that the organization has the information and the systems it
needs to support its operations. Information systems professionals are also involved in designing
technology-based organizational communication and collaboration systems.
A majority of Information Systems (IS) programs are located in business schools. All IS degrees
combine business and computing coursework. A variety of IS programs exist under various labels which
often reflect the nature of the program. For example, programs in Computer Information Systems usually
have the strongest technology focus, while programs in Management Information Systems emphasize the
organizational and behavioral aspects of IS. Degree program names are not always consistent.
2.3.4. Information Technology
Information technology is a label that has two meanings. In the broadest sense, the term information
technology is often used to refer to all of computing. In academia, it refers to undergraduate degree
programs that prepare students to meet the computer technology needs of business, government,
healthcare, schools, and other kinds of organizations. In some nations, other names are used for such
degree programs.
In the previous section, we said that Information Systems focuses on the information aspects of
information technology. Information Technology is the complement of that perspective: its emphasis is
on the technology itself more than on the information it conveys. IT is a new and rapidly growing field
that started as a grassroots response to the practical, everyday needs of business and other organizations.
Today, organizations of every kind are dependent on information technology. They need to have
appropriate systems in place. These systems must work properly, be secure, and upgraded, maintained,
and replaced as appropriate. Employees throughout an organization require support from IT staff who
understand computer systems and their software and are committed to solving whatever computer-related
problems they might have. Graduates of information technology programs address these needs.
Degree programs in information technology arose because degree programs in the other computing
disciplines were not producing an adequate supply of graduates capable of handling these very real needs.
IT programs exist to produce graduates who possess the right combination of knowledge and practical,
hands-on expertise to take care of both an organization’s information technology infrastructure and the
people who use it. IT specialists assume responsibility for selecting hardware and software products

Page 14


appropriate for an organization, integrating those products with organizational needs and infrastructure,
and installing, customizing, and maintaining those applications for the organization’s computer users.
Examples of these responsibilities include the installation of networks; network administration and
security; the design of web pages; the development of multimedia resources; the installation of
communication components; the oversight of email systems; and the planning and management of the
technology lifecycle by which an organization’s technology is maintained, upgraded, and replaced.
2.3.5. Software Engineering
Software engineering is the discipline of developing and maintaining software systems that behave
reliably and efficiently, are affordable to develop and maintain, and satisfy all the requirements that
customers have defined for them. This reflects its origins as outlined in Section 2.2.2. More recently, it
has evolved in response to factors such as the growing impact of large and expensive software systems in
a wide range of situations and the increased importance of software in safety-critical applications.
Software engineering is different in character from other engineering disciplines due to both the
intangible nature of software and the discontinuous nature of software operation. It seeks to integrate the
principles of mathematics and computer science with the engineering practices developed for tangible,
physical artifacts. Prospective students can expect to see software engineering presented in two contexts.
• Degree programs in computer science offer one or more software engineering courses as elements of
the CS curriculum. Some offer a multi-course concentration in software engineering within CS.
• A number of institutions offer a software engineering degree program.
Degree programs in computer science and in software engineering have many courses in common.
Software engineering students learn more about software reliability and maintenance and focus more on
techniques for developing and maintaining software that is correct from its inception. While CS students
are likely to have heard of the importance of such techniques, the engineering knowledge and experience
provided in SE programs go beyond what CS programs can provide. The importance of this fact is so
great that one of the recommendations of the SE report is that, during their program of study, students of
SE should participate in the development of software to be used in earnest by others. SE students learn
how to assess customer needs and develop usable software that meets those needs. Knowing how to
provide genuinely useful and usable software is of paramount importance.
In the workplace, the term software engineer is a job label. There is no standard definition for this term
when used in a job description. Its meaning varies widely among employers. It can be a title equivalent to
computer programmer or a title for someone who manages a large, complex, and/or safety-critical
software project. The layman must be mindful not confuse the discipline of software engineering with the
ambiguous use of the term software engineer as used in employment advertisements and job titles.

2.4. Snapshots: Graphical Views of the Computing Disciplines
To illustrate the commonalities and differences among computing disciplines, we have created graphic
characterizations of them. They suggest how each discipline occupies the problem space of computing as
shown in Figure 2.2. They represent current realities, not ambitions for the future. The focus is on what
students in each of the disciplines typically do after graduation, not on all topics a student might study.
Some individuals will have career roles that go beyond the scenarios described by these snapshots.
The horizontal range runs from Theory, Principles, Innovation on the left, to Application, Deployment,
Configuration on the right. Thus, someone who likes the idea of working in a laboratory to invent new
things or in a university to develop new principles will want to work in a discipline that occupies the
space to the left. Conversely, someone who wants to help people choose and use appropriate technology
or who wants to integrate off-the-shelf products to solve organizational problems will want an area that

Page 15


occupies space to the right. Because there are many kinds of job tasks that fall between the extremes, one
should not just look only at the far left and far right but also consider possibilities between the extremes.
The vertical range runs from Computer Hardware and Architecture at the bottom, to Organizational Issues
and Information Systems at the top. As we go up this axis, the focus is on people, information, and the
organizational workplace. As we move down on this axis, the focus is on devices and the data shared
among them. Thus, someone who likes designing circuits or is curious about a computer’s inner
workings will care about the lower portions; someone who wants to see how technology can work for
people, or who is curious about technology’s impact on organizations, will care about the upper portions.
We can consider the horizontal and vertical dimensions together. Someone who cares about making
things work for people and is more interested in devices than organizations will be interested in the lower-
right, while someone who wants to develop new theories about how information affects organizations will
be interested in the upper-left, and so on.
In Figures 2.3 through 2.7, we use this framework to sketch out the conceptual territory occupied by each
of the five computing disciplines. These are informal illustrations used to communicate the task force’s
subjective interpretation of the various disciplines. They are not based on any precise quantitative
foundation. Furthermore, they show only computing topics. Both computer engineering and information
systems programs devote significant attention to topics that are outside of computing and not reflected in
this diagram. Tables of required computing and non-computing topics are provided in Chapter 3.

Organizational Issues
& Information Systems

Application
Technologies

Software Methods
and Technologies

Systems
Infrastructure

Computer Hardware
and Architecture

Theory DEVELOPMENT Application
Principles Deployment
Theory Application
Deployment
More Theoretical More Applied

Figure 2.2. The Problem Space of Computing

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The shaded portion in Figure 2.3 represents the computer engineering discipline. It is broad across the
bottom because computer engineering covers the range from theory and principles to the practical
application of designing and implementing products using hardware and software. It narrows towards the
center as we move upwards because a computer engineer’s interests narrow as we move away from the
hardware. By the time we get up to the level of software development, we see that the computer
engineer’s interest has narrowed to the horizontal center because they care about software only inasmuch
as they need it to develop integrated devices.


Application
Technologies

Software Methods
and Technologies

Systems
Infrastructure

Computer Hardware
and Architecture

Innovation Configuration

CE

Figure 2.3. Computer Engineering

Page 17


The shaded portion in Figure 2.4 represents the computer science discipline. Computer science covers
most of the vertical space between the extreme top and extreme bottom because computer scientists
generally do not deal with just the hardware that runs software, or just the organization that makes use of
the information that computing can provide. As a group, computer scientists care about almost
everything in between those areas (down as far as the software that enables devices to work and up as far
as the information systems that help organizations to operate). They design and develop all types of
software from systems infrastructure (operating systems, communications programs, etc.) to application
technologies (web browsers, databases, search engines, etc.) Computer scientists create these capabilities,
but they do not manage the deployment of them. Therefore, the shaded area for computer science
narrows and then stops as we move to the right. This is because computer scientists do not help people to
select computing products, or tailor products to organizational needs, or learn to use such products.


Application
Technologies

Software Methods
and Technologies

Systems
Infrastructure

Computer Hardware
and Architecture


CS
Figure 2.4. Computer Science

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The shaded portion in Figure 2.5 represents the information systems discipline. The shaded area extends
across most of the top-most level because IS people are concerned with the relationship between
information systems and the organizations that they serve, extending from theory and principles to
application and development. Many IS professionals are also involved in system deployment and
configuration and the training of users. The area covered by IS dips downward, all the way through
software development and systems infrastructure in the right half of the graph. This is because IS
specialists often tailor application technologies (especially databases) to the needs of the enterprise, and
they often develop systems that utilize other software products to suit their organizations’ needs for
information. (This figure does not reflect the attention that information systems programs devote to core
business topics. See Chapter 3 for tables that summarize both computing and non-computing topics.)


Application
Technologies

Software Methods
and Technologies

Systems
Infrastructure

Computer Hardware
and Architecture


IS

Figure 2.5. Information Systems

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The shaded portion in Figure 2.6 represents the information technology discipline. Its shaded area
extends down most of the right edge as it focuses on the application, deployment, and configuration needs
of organizations and people over a wide spectrum. Across this range (from organizational information
systems, to application technologies and down to systems infrastructure), their role has some overlap with
IS, but IT people have a special focus on satisfying human needs that arise from computing technology.
In addition, the IT shaded area goes leftwards from application towards theory and innovation, especially
in the area of application technologies. This is because IT people often develop the web-enabled digital
technologies that organizations use for a broad mix of informational purposes, and this implies an
appropriate conceptual foundation in relevant principles and theory.
Because IT is a very new discipline, its focus has been on developing educational programs that give
students a foundation in existing concepts and skills. Many in the community of IT faculty assert that
research in their field will grow to create and develop new knowledge in relevant areas. When that
happens, an appropriate snapshot would feature a shaded area that extends significantly further to the left.
However, this is an ambition and not yet an achievement. This figure reflects the current status of IT.


Application
Technologies

Software Methods
and Technologies

Systems
Infrastructure

Computer Hardware
and Architecture


IT

Figure 2.6. Information Technology

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The shaded portion in Figure 2.7 represents the software engineering discipline. Just as we have seen that
computer engineering’s area spans the entire horizontal dimension at the lower hardware-related level,
and IS spans most of that dimension at the higher organization-related level, software engineering covers
a wide range with respect to the systematic development of software. This is because SE people fill a
wide range of needs in large-project software expertise. SE’s main goal is to develop systematic models
and reliable techniques for producing high-quality software on time and within budget, and these
concerns extend all the way from theory and principles to daily practice. The domain of SE also extends
downward through systems infrastructure since SE people develop software infrastructure that is robust in
operation. Its domain also extends upward into organizational issues because SE people are interested in
designing and developing information systems that are appropriate to the client organization.


Application
Technologies

Software Methods
and Technologies

Systems
Infrastructure

Computer Hardware
and Architecture


SE More Theoretical More Applied

Figure 2.7. Software Engineering

Page 21



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Chapter 3: Degree Programs & Career Requirements
In this chapter, we summarize the characteristics of degree programs in each of the five major disciplines
and compare them to each other in terms of both (a) the relative focus of coverage within degree
programs, and (b) the capabilities we expect graduates to have. We then discuss the status and pace of
institutional response to the development of the computing disciplines. After summarizing the
relationship between degree programs and professional career opportunities, we summarize the elements
that are common to all computing degree programs.

3.1. Curriculum Summaries: A Tabular View of Computing Degree Programs
Graphical views are good for conveying information at a glance but, by their nature, they are incomplete
in detail and can give imprecise impressions. In this section, we provide a comparison of the computing
disciplines for those who want more detail.
Table 3.1 provides a comparative view of the emphasis on computing topics among the five kinds of
degree programs covered. The left column contains a list of 40 topics that represent areas of computing
knowledge and skill that students study in computing degree programs. This list approximates a union of
the computing topics specified in the five major computing curriculum reports and, thus, provides a
summary of the topics studied at the undergraduate level in one or more of the computing disciplines. If
you are unfamiliar with the topics, you may consult the glossary of topics provided at the end of this
document. The various curriculum reports sometimes use different language for a given topic. They also
differ in the extent to which they break down a topic into subtopics. As a result, the list of topics
provided in Table 3.1 is not an exact match with the topic list of any of the curriculum reports. Rather, it
is a summary of topics specified across the five undergraduate computing curriculum reports.
Table 3.2 provides a similar view concerning the relative emphasis on 17 non-computing topics across the
five kinds of computing degrees. While the curriculum guidelines for each of the five kinds of computing
degree mandate coverage of some non-computing topics, two of the computing disciplines lie at the
boundary between computing and other disciplines. Computer engineering includes elements of both
computer science and electrical engineering. The information systems discipline spans the boundary
between computing and business. Thus, students in these two degree programs devote a significant
amount of study to non-computing topics as shown in Table 3.2.
In both tables, the leftmost column lists topics, and the other columns show numerical values per topic for
each of the five kinds of computing degree programs. These values range between 0 (lowest) and 5
(highest) and represent the relative emphasis each kind of computing degree program might be reasonably
expected to place on each given topic. The values in the tables are only illustrative. They are not
intended to represent exact measures of the emphasis each discipline pays to these topics.
For each of the five kinds of degree programs, each topic contains two values: one in the “min” column
and one in the “max” column.
• The min value represents the minimum emphasis typically placed on that topic as specified in the
curriculum report for that computing discipline. The min value indicates a discipline’s minimum
requirement relative to the minimum requirements of the other disciplines.
• The max value represents the greatest emphasis that can typically occur within the latitude provided by
the curriculum report for that degree. Each discipline permits students some latitude in choosing an
area of specialization and requires that a student’s program of study go beyond the minimums defined
in the curriculum report. The report also permits each institution to establish requirements greater than
those defined in the five curriculum reports. The max value indicates what one might reasonably
expect of those who concentrate on the topic within the limits implied by other degree requirements.

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Table 3.1: Comparative weight of computing topics across the five kinds of degree programs

CE CS IS IT SE
Knowledge Area
min max min max min max min max min max
Programming Fundamentals 4 4 4 5 2 4 2 4 5 5
Integrative Programming 0 2 1 3 2 4 3 5 1 3
Algorithms and Complexity 2 4 4 5 1 2 1 2 3 4
Computer Architecture and Organization 5 5 2 4 1 2 1 2 2 4
Operating Systems Principles & Design 2 5 3 5 1 1 1 2 3 4
Operating Systems Configuration & Use 2 3 2 4 2 3 3 5 2 4
Net Centric Principles and Design 1 3 2 4 1 3 3 4 2 4
Net Centric Use and configuration 1 2 2 3 2 4 4 5 2 3
Platform technologies 0 1 0 2 1 3 2 4 0 3
Theory of Programming Languages 1 2 3 5 0 1 0 1 2 4
Human-Computer Interaction 2 5 2 4 2 5 4 5 3 5
Graphics and Visualization 1 3 1 5 1 1 0 1 1 3
Intelligent Systems (AI) 1 3 2 5 1 1 0 0 0 0
Information Management (DB) Theory 1 3 2 5 1 3 1 1 2 5
Information Management (DB) Practice 1 2 1 4 4 5 3 4 1 4
Scientific computing (Numerical mthds) 0 2 0 5 0 0 0 0 0 0
Legal / Professional / Ethics / Society 2 5 2 4 2 5 2 4 2 5
Information Systems Development 0 2 0 2 5 5 1 3 2 4
Analysis of Business Requirements 0 1 0 1 5 5 1 2 1 3
E-business 0 0 0 0 4 5 1 2 0 3
Analysis of Technical Requirements 2 5 2 4 2 4 3 5 3 5
Engineering Foundations for SW 1 2 1 2 1 1 0 0 2 5
Engineering Economics for SW 1 3 0 1 1 2 0 1 2 3
Software Modeling and Analysis 1 3 2 3 3 3 1 3 4 5
Software Design 2 4 3 5 1 3 1 2 5 5
Software Verification and Validation 1 3 1 2 1 2 1 2 4 5
Software Evolution (maintenance) 1 3 1 1 1 2 1 2 2 4
Software Process 1 1 1 2 1 2 1 1 2 5
Software Quality 1 2 1 2 1 2 1 2 2 4
Comp Systems Engineering 5 5 1 2 0 0 0 0 2 3
Digital logic 5 5 2 3 1 1 1 1 0 3
Embedded Systems 2 5 0 3 0 0 0 1 0 4
Distributed Systems 3 5 1 3 2 4 1 3 2 4
Security: issues and principles 2 3 1 4 2 3 1 3 1 3
Security: implementation and mgt 1 2 1 3 1 3 3 5 1 3
Systems administration 1 2 1 1 1 3 3 5 1 2
Management of Info Systems Org. 0 0 0 0 3 5 0 0 0 0
Systems integration 1 4 1 2 1 4 4 5 1 4
Digital media development 0 2 0 1 1 2 3 5 0 1
Technical support 0 1 0 1 1 3 5 5 0 1

Again, min represents the minimum called for by the curriculum guidelines, and max represents the
greatest emphasis one might expect in the typical case of a student who chooses to undertake optional
work in that area or who graduates from an institution that requires its students to achieve mastery beyond
that required by the curriculum reports. Because the difference between the min and max values can be
large, programs with the same degree name may differ substantially because of the local choices made in
determining their requirements. Both min and max values refer to what can be reasonably expected in the
general case. For any individual student or degree program, the min value might be as low as zero and
the max value might be as high as five, regardless of prevailing curricular standards.
3.1.1. How the Table Values Were Determined
Tables 3.1 and 3.2 represent the consensus of judgment reached by the CC2005 Joint Task Force. The
task force formulated this consensus from an examination of the discipline-specific body of knowledge
found in the most recent curriculum volume for each of the computing disciplines: computer engineering,

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Table 3.2: Comparative weight of non-computing topics across the five kinds of degree programs
CE CS IS IT SE
Knowledge Area
min max min max min max min max min max
Organizational Theory 0 0 0 0 1 4 1 2 0 0
Decision Theory 0 0 0 0 3 3 0 1 0 0
Organizational Behavior 0 0 0 0 3 5 1 2 0 0
Organizational Change Management 0 0 0 0 2 2 1 2 0 0
General Systems Theory 0 0 0 0 2 2 1 2 0 0
Risk Management (Project, safety risk) 2 4 1 1 2 3 1 4 2 4
Project Management 2 4 1 2 3 5 2 3 4 5
Business Models 0 0 0 0 4 5 0 0 0 0
Functional Business Areas 0 0 0 0 4 5 0 0 0 0
Evaluation of Business Performance 0 0 0 0 4 5 0 0 0 0
Circuits and Systems 5 5 0 2 0 0 0 1 0 0
Electronics 5 5 0 0 0 0 0 1 0 0
Digital Signal Processing 3 5 0 2 0 0 0 0 0 2
VLSI design 2 5 0 1 0 0 0 0 0 1
HW testing and fault tolerance 3 5 0 0 0 0 0 2 0 0
Mathematical foundations 4 5 4 5 2 4 2 4 3 5
Interpersonal communication 3 4 1 4 3 5 3 4 3 4

computer science, information systems, information technology, and software engineering. It used the
results of this examination to define the topical elements of the two tables. That examination also heavily
influenced the numerical values assigned to each topic for each discipline. The discipline-specific bodies
of knowledge provide some quantifiable data concerning the minimum coverage called for by each
discipline for each topic. However, they do not provide information that is sufficient to permit any useful
calculation of the relative emphasis each discipline places on a given topic.

To generate useful indications of the relative emphasis each discipline places on a given topic, it was
necessary that we apply our best judgment as to how to integrate various hard and soft factors into a
meaningful metric. Hard factors are the numerical specifications found in the discipline-specific bodies
of knowledge. Soft factors include:
• differences in the perspective endemic to the various computing disciplines. Each of the computing
disciplines has its own unique perspective and agenda as characterized in Sections 2.2 and 2.3.
• differences in the meanings attached to seemingly identical terms. While each computing discipline
includes coverage of numerous computing topics, discipline-specific perspectives have the effect of
attaching different meanings to the same term. For example, while each discipline requires study of
mathematical foundations, programming fundamentals, networking, operating systems, etc., the precise
set of knowledge and skills associated with these topics varies-sometimes widely-among the
disciplines. This issue is addressed more fully in Sections 3.2 and 3.3 and in Table 3.3. In light of the
inconsistent use of terms, the only certain way to be clear about what a given topic area means for a
given computing discipline is to consult the curriculum volume for that discipline.
• differences in the latitude for studying optional topics. Despite efforts to make each of the five
discipline-specific curriculum reports international in scope, most are implicitly oriented to the U.S.
system of defining undergraduate degree programs. In the U.S. system, the amount of technical study
required for a degree program in most subjects is limited by the requirement to have a significant
general education component in all degree programs. Such limitations affect all computing degree
programs. In addition to this generic U.S. constraint, some computing degree programs must devote a
greater portion of their limited resources to specific topics which, in turn, limits how much freedom is
available to study computing topics that are not required for the degree. For example, degree programs
in computer engineering must devote significant study to topics required by (a) the engineering
profession, and (b) the CE emphasis on hardware-related topics. This curtails how much study CE

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students may devote to optional computing topics. Degree programs in information systems face
similar limitations due to the requirement that IS students study business and organizational topics.
The fact that not all computing disciplines have equal flexibility places constraints on degree programs
that are difficult to translate in any precise way into our schema of min and max topical coverage.
Due to the range and nature of these factors, the numerical values assigned in Tables 3.1 and 3.2 reflect a
synthesis of hard and soft factors constructed by the CC2005 Task Force. As such they are fuzzy
numbers. One important reality-check is that each numerical value for each topic for each given
discipline was deemed satisfactory not only by the representative of that computing discipline but also by
the representatives of each of the other computing disciplines. Thus, each value is neither so low as to be
unacceptable to the representative of the discipline in question, nor so high that representatives of other
discipline found it unjustified.
3.1.2. Using the Table: Two Related Examples
To see how to use Table 3.1, we will consider the fourth and fifth topics in the table: “Operating Systems
- Principles and Design” and “Operating Systems - Configuration and Use”. Both topics concern
operating systems. A reader who is not familiar with the terminology may wish to consult the Glossary.
• Readers who are unsure what operating systems are can learn from the glossary that the term operating
system refers to a specific kind of software (such as Windows, Linux, UNIX, Mac OS, etc.) that
permits the human user to interact with a computer. It also enables a computer to manage its resources
(memory, disk drives, monitor screen, network interface, etc.) so that it can run whatever application
programs (word processor, spreadsheet, web browser, etc.) the user asks the computer to run. In short,
an operating system is software that runs in the background, permitting the computer to operate in
useful ways.
• A reader can also learn from the glossary that the topic Operating Systems - Principles and Design
refers to foundational knowledge that enables a student to understand the tasks an operating system
must perform. It includes the various strategies and tactics that an operating system might employ to
do these things, including the kinds of mechanisms that the operating systems designer can use to
implement these strategies and tactics, the strengths and weaknesses of various popular approaches,
and so on. In addition to mastering the foundational knowledge of the tasks of an operating system, we
expect that a student will complete a major programming project, either creating an operating system
from scratch or creating a significant enhancement to an existing operating system.
• Similarly, the reader can learn from the glossary that the topic Operating Systems - Configuration and
Use is concerned with the practical mastery of the capabilities of mainstream operating system
products. Rather than focus on the underlying concepts and principles for designing and implementing
operating systems, this topic focuses on developing the student’s ability to make full use of the various
capabilities provided by existing operating systems. The goal is to produce students who know the
strengths and limitations of two or more mainstream operating systems, understand how the attributes
of the systems relate to both organizational policy and individual user needs, and know how to use the
operating systems capabilities to satisfy user needs and implement organizational policy.
The reader can consult Table 3.1 to see how the various disciplines compare in the emphasis they place
on each of these two topics.
• For the topic Operating Systems (OS) – Principles and Design, we see that both information systems
and information technology programs give it less emphasis than computer engineering, computer
science, and software engineering programs do. For typical degree programs in IS and IT, both the min
and max values are 1, which indicates that students in these programs are exposed to some basic
concepts and terminology but typically do not study OS principles and design in any substantive way.
In contrast, CE, CS, and SE programs have higher min and max values, indicating that they have higher

Page 26


minimum standards and a higher ceiling for student mastery. The fact that a higher min value is shown
for CS and SE (3 each) than is shown for CE (2) indicates that the CS and SE curricula typically feature
more coverage of OS principles and design than CE programs do. The fact that a higher max value is
shown for CS (5) than for CE and SE (4 each) indicates that CS curricula typically have more room in
their program of study to permit in-depth coverage of OS principles and design for those who want to
study it.
• For the topic Operating Systems (OS) – Configuration and Use, we see a different pattern of relative
emphasis among the degree programs. While all degree programs provide some experience in using
and configuring operating systems, IT programs have the highest min and max values (3 and 5,
respectively). This indicates that IT programs focus their coverage of OS on configuration and use, and
expect all their students to obtain significant capability in this area. The other degree programs have
weaker minimum expectations (2 each) that are comparable to each other. There is slightly more room
in CS and SE programs for optional mastery of this topic (max 4 each) than in CE and IS programs
(max 3 each), but all place less emphasis on OS configuration and use than IT programs do.
The comparison provided in Table 3.1 allows us to conclude that a student who wants to understand the
principles and design of operating systems will typically not be well served by IS and IT programs, will
be better satisfied by CE, CS, or SE programs, and will have the greatest opportunity for in-depth study in
CS programs. In contrast, a student who is interested primarily in the practical configuration and use of
operating systems will be served best by an IT program since each of the other degree programs provides
less opportunity for in-depth mastery in this area. A student wishing to pursue both OS topics would
likely gravitate toward a CS or SE degree program where he or she will sacrifice depth with respect to
practical application in order to obtain a better balance of principles and application.

3.2. Degree Outcomes: Comparing Expectations of Program Graduates
The previous section provides a comparative view of the emphasis of study in the five major kinds of
computing degree programs. This section provides a comparative view of the performance capabilities
expected of the graduates of each degree program. The previous section summarizes what a student will
study; this section summarizes the expectation of the student after graduation.
Table 3.3 lists nearly 60 performance capabilities across 11 categories. For each capability, each
discipline is assigned a value from 0 to 5. The value 0 represents no expectation whatsoever, while 5
represents the highest relative expectation. As with the values of Tables 3.1 and 3.2, these values are
fuzzy numbers (determined as described at the end of Section 3.1.1). Table 3.3 shows that
• computer engineers should be able to design and implement systems that involve the integration of
software and hardware devices;
• computer scientists should be prepared to work in a broad range of positions involving tasks from
theoretical work to software development;
• information systems specialists should be able to analyze information requirements and business
processes and be able specify and design systems that are aligned with organizational goals;
• information technology professionals should be able to work effectively at planning, implementation,
configuration, and maintenance of an organization’s computing infrastructure; and
• software engineers should be able to properly perform and manage activities at every stage of the life
cycle of large-scale software systems.
In contrast to Tables 3.1 and 3.2 that summarize the inputs provided to students by degree programs,
Table 3.3 focuses on outputs, summarizing the relative capability expectations of graduates.

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Table 3.3. Relative performance capabilities of computing graduates by discipline
Area Performance Capability CE CS IS IT SE
Algorithms Prove theoretical results 3 5 1 0 3
Develop solutions to programming problems 3 5 1 1 3
Develop proof-of-concept programs 3 5 3 1 3
Determine if faster solutions possible 3 5 1 1 3
Application programs Design a word processor program 3 4 1 0 4
Use word processor features well 3 3 5 5 3
Train and support word processor users 2 2 4 5 2
Design a spreadsheet program (e.g., Excel) 3 4 1 0 4
Use spreadsheet features well 2 2 5 5 3
Train and support spreadsheet users 2 2 4 5 2
Computer programming Do small-scale programming 5 5 3 3 5
Do large-scale programming 3 4 2 2 5
Do systems programming 4 4 1 1 4
Develop new software systems 3 4 3 1 5
Create safety-critical systems 4 3 0 0 5
Manage safety-critical projects 3 2 0 0 5
Hardware and devices Design embedded systems 5 1 0 0 1
Implement embedded systems 5 2 1 1 3
Design computer peripherals 5 1 0 0 1
Design complex sensor systems 5 1 0 0 1
Design a chip 5 1 0 0 1
Program a chip 5 1 0 0 1
Design a computer 5 1 0 0 1
Human-computer interface Create a software user interface 3 4 4 5 4
Produce graphics or game software 2 5 0 0 5
Design a human-friendly device 4 2 0 1 3
Information systems Define information system requirements 2 2 5 3 4
Design information systems 2 3 5 3 3
Implement information systems 3 3 4 3 5
Train users to use information systems 1 1 4 5 1
Maintain and modify information systems 3 3 5 4 3
Information management Design a database mgt system (e.g., Oracle) 2 5 1 0 4
(Database) Model and design a database 2 2 5 5 2
Implement information retrieval software 1 5 3 3 4
Select database products 1 3 5 5 3
Configure database products 1 2 5 5 2
Manage databases 1 2 5 5 2
Train and support database users 2 2 5 5 2
IT resource planning Develop corporate information plan 0 0 5 3 0
Develop computer resource plan 2 2 5 5 2
Schedule/budget resource upgrades 2 2 5 5 2
Install/upgrade computers 4 3 3 5 3
Install/upgrade computer software 3 3 3 5 3
Intelligent systems Design auto-reasoning systems 2 4 0 0 2
Implement intelligent systems 2 4 0 0 4
Networking and Design network configuration 3 3 3 4 2
communications Select network components 2 2 4 5 2
Install computer network 2 1 3 5 2
Manage computer networks 3 3 3 5 3
Implement communication software 5 4 1 1 4
Manage communication resources 1 0 3 5 0
Implement mobile computing system 5 3 0 1 3
Manage mobile computing resources 3 2 2 4 2
Systems Development Manage an organization’s web presence 2 2 4 5 2
Through Integration Configure & integrate e-commerce software 2 3 4 5 4
Develop multimedia solutions 2 3 4 5 3
Configure & integrate e-learning systems 1 2 5 5 3
Develop business solutions 1 2 5 3 2
Evaluate new forms of search engine 2 4 4 4 4

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3.3. International Differences
This report and the five other volumes of the Computing Curricula Series on which it is based have
benefited to some degree from international input especially from the United Kingdom. Our goal has
been to provide advice and illustrations that would have international relevance. While our future efforts
must feature significantly expanded international participation, we can claim some measure of success as
some interesting points of comparison arose. There are differences in the structure of the academic year,
in the emphasis given to the study of computing within a degree program (e.g., in the U.K. almost all
courses in a computing degree program will be oriented toward computing), in the quality control
mechanisms (e.g., different expectations and practices with regard to accreditation as discussed in section
4.5), and so on. In addition, there are different approaches to defining the focus of degree programs.

• In the US, there is a very strong sense of a core for each discipline. The core for each discipline
is intended as a specification of those elements of the discipline that are deemed fundamental and
which all students of that discipline should fully understand. This approach has at least two
benefits: it helps to create a shared understanding of the abilities that can be expected of
graduates, and it facilitates transfer between institutions. Argument and eventual agreement about
the definition of the core help to support strong discipline definitions and a clear understanding of
the meaning of degree titles.

• The idea of a core is far less prominent in countries such as the U.K where degree titles are seen
as providing strong marketing opportunities. As a result, by U.S. standards, the U.K offers a
much larger variety of computing degree program names. The rich variety of degree titles
reflects different emphases and different career opportunities. In the U.K, guidance and quality
issues associated with degrees are taken care of by criteria and mechanisms such as those outlined
in Section 3.5
The Joint Task Force did not have access to sufficient information about models from other nations. A
thorough evaluation of various approaches applied around the globe is an important step for future work.

3.4. The Pace of Change in Academia: Disciplines and Available Degrees
As discussed previously, the landscape of the computing degree programs has undergone dramatic change
as a result of the explosion of computing during the 1990s. The computing field has evolved to the point
that we are seeing the emergence of degree programs that are focused on the challenges that now confront
both the computing profession and our computing-dependent society as a whole.
The evolution of computing discussed in Chapter 2 is often not reflected in the kinds of degree programs
that are offered. Very few North American colleges and universities offer all five major kinds of
computing degrees. The two newer kinds of degrees, IT and SE, are less common than are degrees in the
more established disciplines of CE, CS, and IS. Institutions tend to be cautious and conservative, and the
complex nature of academic degree programs means that it is difficult to implement significant changes
rapidly. Thus at some institutions, the choices of computing degree programs look more like the pre-
1990s view shown in the top portion of Figure 2.1 than the post-1990s view. This is because the pace of
change in computing is quite rapid, while the pace of institutional change generally can be quite slow.
This natural institutional lag can create problems for students who are trying to choose a computing-
related degree program that fits their interests and goals. It can also create problems for educators who
are trying to ensure that their educational programs are providing up-to-date programs that serve their
constituents. At many institutions, the faculty seeks to minimize this lag by using the final year of a
degree program to offer students a chance to learn about areas of cutting-edge specialization and research.

Page 29


Despite the natural lag, there is widespread evidence that important and fundamental changes have taken
place. In looking at the development of computing over the last twenty years or so, one can observe that
there has been a dramatic shift in emphasis towards interaction and perhaps away from the study of the
algorithm. The move towards interaction can be viewed as an important mark of computing’s success: it
highlights the fact that a broad range of people are now using and interacting with computers to a far
greater degree than in the early days. It is very natural therefore that new programs of study reflect this
fact, and both the large number of IS programs and the recent emergence of IT programs are
manifestations of this. Indeed, there is scope for an even richer variety of possibilities, and we fully
expect to see change in computing continue.
Because institutional lag has consequences, it is important that readers of this report recognize its
existence and look for indications that a given institution is taking steps to overcome it. In general terms,
there are certain metrics or marks of quality which suggest that institutional lag is not a serious problem
for a given program or department. Among these indicators are:
• the existence of an active advisory board that features the involvement of advisors from industry;
• the involvement of students in committees that vet programs and help define goals for change;
• institutional quality control mechanisms which actively seek and obtain advice from external experts;
• employment statistics of graduates that can provide indications of the reputation of a program’s
graduates and of the institution itself; and
• accreditation of degree programs (discussed in Section 4.5) that provides a mark of quality and
addresses issues such as the currency of the program of study.
Beyond this, there are discipline-specific considerations which we now summarize.
The change from the pre-1990s view of computing to the post-1990s view typically includes a more
complete emergence of computer engineering from within the electrical engineering discipline. Most
often, both kinds of programs exist in the same academic department, although many computer
engineering programs reside in joint departments of computer science and engineering. Though not true
on the international stage, in the U.S., there has always been a single home for those who study computer
hardware. It used to be electrical engineering. It has become computer engineering. At most universities,
the change from the pre-1990s to post-1990s view has already taken place. However, even some of the
very best universities do not offer a separate computer engineering program. At some universities,
electrical engineering and computer science reside in the same school, and computer engineering is seen
as a natural merging of interests among faculty in these two disciplines. If a given institution’s
departmental structure does not feature an explicit recognition of computer engineering, it does not
necessarily imply any shortcoming.
There are notably fewer programs in computer engineering than in computer science or information
systems. In the U.S., this is because most American colleges and universities do not offer engineering
programs of any kind. American engineering programs reside disproportionately in relatively large
universities or specialized institutes that can meet the requirements for offering accredited engineering
degrees. We do not expect this to change significantly in the future.
In the U.S., there are far more degree programs in computer science than in any other computing
discipline. The great majority of colleges and universities offer a CS degree. To some extent, this is a
historical artifact: computer science was the only substantive computing discipline that focused explicitly
on software development when academic computing degree programs emerged in the 1970s. When most

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colleges created their computing degree programs, computer science was the only choice that had strong
ties to mathematics, science, and/or engineering. (IS programs developed around the same time but their
primary ties were to business schools.) At smaller colleges, the CS degree program may be housed in a
mathematics and CS department but almost all of these departments offer two distinct degree programs.
The increased diversity we see in the post-1990s computing disciplines is fairly localized in areas that
affect computer science. The new computing disciplines target career areas that traditionally have been
filled by graduates of CS programs.
Currently, there is an ongoing discussion regarding the relationship between what computer science
programs teach and what most graduates of computer science actually do in their careers. To understand
this discussion, it is necessary to review the characterization of computer science provided in Section
2.3.2. The work of computer scientists falls into three categories: designing and implementing software;
devising new ways to use computers; and developing effective ways to solve computing problems. Let us
consider what is involved in a career path in each area.
• Career Path 1: Designing and implementing software. This refers to the work of software development
which has grown to include aspects of web development, interface design, security issues, mobile
computing, and so on. This is the career path that the majority of computer science graduates choose.
While a bachelor’s degree is generally sufficient for entry into this kind of career, many software
professionals return to school to obtain a terminal master’s degree. (Rarely is a doctorate involved.)
Career opportunities occur in a wide variety of settings including large or small software companies,
large or small computer services companies, and large organizations of all kinds (industry, government,
banking, healthcare, etc.). Degree programs in software engineering also educate students for this
career path.
• Career Path 2: Devising new ways to use computers. This refers to innovation in the application of
computer technology. A career path in this area can involve advanced graduate work, followed by a
position in a research university or industrial R&D lab, or it can involve entrepreneurial activity such as
was evident during the dot-com boom of the 1990s, or it can involve a combination of the two.
• Career Path 3: Developing effective ways to solve computing problems. This refers to the application
or development of computer science theory and knowledge of algorithms to ensure the best possible
solutions for computationally intensive problems. As a practical matter, a career path in the
development of new computer science theory typically requires graduate work to the Ph.D. level,
followed by a position in a research university or an industrial R&D laboratory.
Computer science programs generally intend to prepare students for these three career paths. In addition,
there is a fourth career path that CS programs do not target but nonetheless draws many computer science
graduates.
• Career Path 4: Planning and managing organizational technology infrastructure. This refers to the
work for which the new information technology (IT) programs explicitly aim to educate students.
Of these four career paths, career paths 2 and 3 are important elements of the identity of computer science
and are the kind of career paths that many computer science faculty wish to see their students choose. As
a practical observation, however, only an extremely small minority of the students who earn computer
science bachelor’s degrees actually choose them. For those few who do, institutional lag is not an issue: a
strong bachelor’s degree program in computer science, followed by graduate study (probably to the
doctoral level) is clearly the preferred choice.
Career paths 1 and 4 are the focus of debate. These careers draw the overwhelming majority of computer
science graduates. They are also the focus of the new computing degree programs (software engineering
and information technology, respectively) which have emerged to provide more focused alternatives to

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computer science programs in preparing students for these career paths. In addition, a significant number
of graduates in information systems have, over the years, selected organizational roles that are very
similar to these career paths. No resolution has yet occurred to the debate about the relative value of
computer science programs vs. software engineering and information technology programs. However,
the issues that arise in the debate are well defined and are discussed in the subsequent subsections on
software engineering and information technology, respectively. For career paths 1 and 4, one should
evaluate the relative value of computer science programs in the light of the emergence of degree programs
in the two new computing disciplines.
The change in the role of information systems concerns the expanded role of information technology in
organizations of all kinds. Historically, information systems programs prepared students to work with
functionally oriented business applications such as payroll, accounts receivables, inventory management,
etc. On the technology side, IS students could expect to become familiar with computer applications
related to these traditional business areas especially database management systems, and with spreadsheets
and other off-the-shelf software products that had broad utility to business people.
Modern IS programs focus on the broader role of IT-enabled information utilization and business
processes in a wide range of enterprises, while still maintaining their close association with business
schools. What information does the enterprise need? How is that information generated? Is it delivered
to the people who need it? Is it presented to them in ways that permits them to readily use it? Is the
organization structured to be able to utilize technology effectively? Are the business processes of the
organization well designed? Do they utilize the opportunities created by information technology fully?
Does the organization fully utilize the communication and collaboration capabilities of information
technologies? Is the organization capable of adapting quickly enough to changing external circumstances?
These are the important issues that various types of enterprises increasingly rely on IS people to address.
For IS programs, the traditional role still exists, but it is no longer sufficient. The meaningful question is:
“Has an IS program broadened its scope to include an integrated view of the enterprise with complex
information needs and high-level dependency on IT-enabled business processes?” Web-based distributed
technologies provide the infrastructure for globally connected organizations, and modern IS programs
have to address the needs of such organizations. IS students must learn how to assess and evaluate
organizational information needs, specify information requirements, and design practical systems to
satisfy these requirements. If a program focuses only on the design and development of narrow
functional applications and the use of personal productivity tools, it is seriously behind f the mainstream
IS programs.
In addition to these concerns, IS has to take into account the emergence of IT programs. Traditionally,
many graduates of IS programs have functioned in roles that are similar to the roles for which IT
programs explicitly prepare their students. As the number of IT programs grows, many IS departments
will have to evaluate how to define and serve their core constituents.
In the last few years, degree programs in information technology have emerged and developed to such an
extent that they now should be an important part of any discussion of computing degree programs. As
summarized in Section 2.3.4, IT programs focus on producing graduates who know how to make
information technology work in a wide range of settings. Organizations of all kinds have become
dependent on networked computing infrastructure to such a degree that they cannot function without that
infrastructure. IT people are prepared to select, manage, and maintain that infrastructure, ensuring that it
meets organizational needs. They also create digital content for that infrastructure and take care of the IT
support needs of the individuals who use it.

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The emergence of IT programs represents a grassroots movement by computing educators to respond to
the very real needs of both their local communities and their students. IT programs exist, not because
computer science or information systems programs failed to do their job, but because those disciplines
each define themselves as having a different job. The existence of IT programs reflects one part of the
evolution of career opportunities in computing.
Only a few years ago, computing educators in the U.S. were not familiar with IT degree programs,
although similar programs have existed for years elsewhere. Today, there are many such programs, and
we expect to see this number increase further in the years to come. It was not until 2001 that university-
level IT educators in North America began to organize, and, in the short period since, they have formed a
professional organization, held several conferences, and made substantive progress in developing
curriculum and accreditation guidelines for IT degree programs. It is no exaggeration to say that IT
programs have exploded onto the scene in the U.S.
Some people question whether IT programs are a passing fad. Others ask if IT programs are too technical
in nature to deserve the status of an academic discipline. People asked similar questions about computer
science more than thirty years ago yet, after a number of years, the great majority of North American
colleges began to offer CS degrees. We may well see similar results with respect to IT. IT degree
programs address an important need that is widespread throughout society. To the extent that
organizations rely on computer technology, the IT discipline has a key role to play.
There are two important issues here.
• Rigor. Planning and managing an organization’s IT infrastructure is a difficult and complex job that
requires a solid foundation in applied computing as well as management and people skills. Those in
the IT discipline require special skills – in understanding, for example, how networked systems are
composed and structured, and what their strengths and weaknesses are. There are important software
systems concerns such as reliability, security, usability, and effectiveness and efficiency for their
intended purpose; all of these concerns are vital. These topics are difficult and intellectually
demanding.
• Acceptance. In the U.S., the IT discipline is the new kid on the block and, as a result, faces problems
of acceptance among the more established disciplines. This is a natural phenomenon, and it will take
time and experience for those in the more established computing disciplines to evaluate and recognize
the value that the IT discipline provides. IT is seeking to establish itself as a discipline with its own
intellectual core, a rigorous curriculum, and accreditation guidelines. To the extent that it succeeds at
these challenges, acceptance and respect will naturally follow.
At many institutions, administration is motivated to see an IT program created to respond to community
needs and to provide more choices for prospective students. Whenever an institution creates an IT
program, it must take special care to ensure that it implements the program properly. One must ensure
that the people who are responsible for an IT degree program recognize IT’s importance and are excited
about creating high-quality educational experiences for IT students.
The development of SE is a response to a very real problem: a shortage of degree programs that produce
graduates who can properly understand and develop software systems. CS programs have shown that
they can produce students who have sound skills in programming fundamentals. However, many believe
that they have not been successful at reliably producing graduates able to work effectively on complex
software systems that require engineering expertise beyond the level of programming fundamentals. In
the post-1990s world, many software projects are large and complex, and there is a pressing need for
software engineers who can apply professional practices that ensure that software is reliable, meets the
goals and needs of users, and is produced on schedule and within budget. SE programs represent an effort

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to make the undergraduate experience more successful at providing students with an adequate set of
knowledge and skills for careers as software professionals.
As a practical matter, CS and SE degree programs often have much in common. Both disciplines
recognize that the subject matter of computing has grown to the point where no single degree program
can expect its students to grasp the entire field. Thirty years ago, it was reasonable to expect CS
undergraduates to study everything; now, there is too much of it to fit in a four year (or even five year)
program of study.
Both CS and SE curricula typically require a foundation in programming fundamentals and basic CS
theory. They diverge in what they focus on beyond these core elements. CS programs tend to keep the
core small and then expect students to choose among more advanced courses in areas of CS concentration
(such as systems, networking, database, artificial intelligence, theory, etc.). In contrast, SE programs
generally expect students to focus on a range of topics that are essential to the SE agenda (problem
modeling and analysis, software design, software verification and validation, software quality, software
process, software management, etc.). While both CS and SE programs typically require students to
experience team project activity, SE programs tend to involve the students in significantly more of it, as
effective team processes are essential to effective SE practices. In addition, a key requirement specified
by the SE curriculum guidelines is that SE students should learn how to build software that is genuinely
useful and usable by the customer and satisfies all the requirements defined for it.
Two questions about how SE programs will develop remain unanswered.
• To what extent will degree programs in SE emerge from within CS departments as a side-by-side
alternative to the traditional CS degree? Some believe that such a trend is inevitable, while others do
not believe that such a development is necessary. There remains a difference of opinion among faculty
about the nature and amount of rigorous SE experience that a robust undergraduate education requires
in order to prepare students to function as competent software professionals.
• To what extent will the implications of using the word engineering cause American colleges and
universities to choose a different name for their SE degree programs? In the U.S. and certain other
countries, the professional engineering community is protective of its identity and the word engineering
looms large in that identity. In some states in the U.S. and in Canada, certain uses of the word
engineering are regulated by law. Software engineering differs from the more traditional engineering
disciplines (due to the intangible nature of software and to SE’s focus on human processes rather than
the laws of physics, e.g.). Yet the traditional strength of engineering (robust methods for creating
reliable artifacts) is at the core of the SE agenda. Having the name engineering as part of software
engineering has implications in the U.S. for accreditation and, at some institutions, for the location of
SE within the university. These implications may cause some U.S. programs to shy away from
adopting the name SE. In the U.K., such issues were successfully resolved decades ago.
It appears that most CS students anticipate that their professional careers will involve doing software
development work. We expect that, if a large number of SE degree programs were available as an option
for CS students, many would select it. At present, that choice is not widely available. There are now
about 30 SE degree programs in America. We expect this number to increase, although not at the same
rate that we have seen for IT programs.
Within CS degree programs, the robustness of SE education varies widely. The most recent curriculum
guidelines for CS (CC2001) require some minimal coverage of SE. Most CS degree programs go beyond
the minimum and provide one or more SE courses. Some CS programs offer SE as one of several areas
of CS concentration. When evaluating CS programs that provide such an option, it is important to look
closely at how rigorous that option is.

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3.5. The Pace of Change in the Workplace: Degrees and Career Opportunities
Just as it takes time for academic institutions to adapt, it also takes time for industry and other players in
the computing workplace to do the same. As a result, some job opportunities will reflect the pre-1990s
model shown at the top of Figure 2.3. In other words, because new computing disciplines are new, no
one yet expects people to have those qualifications.
With respect to CE, the new disciplines are not much of an issue. It is clear where people go for expertise
in hardware and related software. CE has adopted this role from EE, and the change is largely complete.
CE, like EE, is part of the professional engineering community, and in the U.S., this has implications for
where one can earn a CE degree. Not every university has an engineering program. Employers looking
for people with a CE background want graduates of an accredited CE program.
It is also clear where people look for expertise at the interface between the information needs of business
and computing. IS occupies that role in both the pre-1990s and post-1990s landscape. It is essential that
those who pursue this path make sure that they find an IS program that continues to update its vision and
has an emphasis that fits the interests of the prospective student. For prospective IS students, the task of
finding the right program is complicated by the variety of names used by such programs.
Most people who now function in the U.S. as serious software engineers have degrees in CS, not in SE.
In large part this is because CS degrees have been widely available for 30 years and SE degrees have not.
The story is similar for people working in the IT profession: most IT professionals who have computing
degrees come from CS or IS programs. It is far too soon for someone who wants to work as a software
engineer or as an information technology practitioner to be afraid that they won’t have a chance if they
don’t graduate from a degree program in one of the new disciplines. In general, a CS degree from a
respected program is the most flexible of degrees and can open doors into the professional worlds of CS,
SE, IT, and sometimes CE. A degree from a respected IS program allows entry to both IS and IT careers.
This situation presents ambiguity to students trying to determine what discipline to study and to educators
who are trying to decide how their programs can best serve their constituents. We identify the various
factors that educators should consider in Chapter 4. We focus on the factors students should consider in
the Guide which is the second part of this report and is also available as a standalone document.
Media attention to outsourcing, offshoring, and job migration has caused many to be concerned about the
future of computing-related careers. It is beyond the scope of this report to address these issues. The
British Computer Society’s report, which addresses these issues as they impact the U.K., is available at:
http://www.bcs.org/BCS/News/PositionsAndResponses/Positions/offshore/offshorereport.htm. ACM’s
Job Migration Task Force is expected to issue a report during the last quarter of 2005. The ACM report is
intended to reflect an international perspective, not just a U.S-centric one. Once completed, the ACM
report will be available at http://www.acm.org/jmtf.

3.6. Shared Identity: Common Requirements of Computing Degrees
As we have seen, each of the major computing disciplines has its own character. Each one is somewhat
different from its siblings in the emphasis, goals, and capabilities of its graduates. Yet they have much in
common. Any reputable computing degree program should include each of the following elements.
1) Essential and foundational underpinnings of its discipline. These may be abstract, for example,
formal theory rooted in mathematics, or they may address professional values and principles.
Regardless of their form or focus, the underpinnings must highlight those essential aspects of the
discipline that remain unaltered in the face of technological change. The discipline’s foundation
provides a touchstone that transcends time and circumstance, giving a sense of permanence and
stability to its educational mission. Students must have a thorough grounding in that foundation.

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2) A foundation in the concepts and skills of computer programming. The foundation has five layers:
a) an intellectual understanding of, and an appreciation for, the central role of algorithms and data
structures;
b) an understanding of computer hardware from a software perspective, for example, use of the
processor, memory, disk drives, display, etc.
c) fundamental programming skills to permit the implementation of algorithms and data structures
in software;
d) skills that are required to design and implement larger structural units that utilize algorithms and
data structures and the interfaces through which these units communicate;
e) software engineering principles and technologies to ensure that software implementations are
robust, reliable, and appropriate for their intended audience.
3) Understanding of the possibilities and limitations of what computer technology (software, hardware,
and networking) can and cannot do. There are three levels:
a) an understanding of what current technologies can and cannot accomplish;
b) an understanding of computing’s limitations, including the difference between what computing is
inherently incapable of doing vs. what may be accomplished via future science and technology;
c) the impact on individuals, organizations, and society of deploying technological solutions and
interventions.
4) Understanding of the concept of the lifecycle, including the significance of its phases (planning,
development, deployment, and evolution), the implications for the development of all aspects of
computer-related systems (including software, hardware, and human computer interface), and the
relationship between quality and lifecycle management.
5) Understanding of the essential concept of process, in at least two meanings of the term:
a) process as it relates to computing especially program execution and system operation;
b) process as it relates to professional activity especially the relationship between product quality
and the deployment of appropriate human processes during product development.
6) Study of advanced computing topics that permits students to visit and understand the frontiers of the
discipline. This is typically accomplished through inclusion of learning experiences that lead students
from elementary topics to advanced topics or themes that pervade cutting-edge developments.
7) The identification and acquisition of skill sets that go beyond technical skills. Such skill sets include
interpersonal communication skills, team skills, and management skills as appropriate to the
discipline. To have value, learning experiences must build such skills (not just convey that they are
important) and teach skills that are transferable to new situations.
8) Exposure to an appropriate range of applications and case studies that connect theory and skills
learned in academia to real-world occurrences to explicate their relevance and utility.
9) Attention to professional, legal, and ethical issues so that students acquire, develop, and demonstrate
attitudes and priorities that honor, protect, and enhance the profession’s ethical stature and standing.
10) Demonstration that each student has integrated the various elements of the undergraduate experience
by undertaking, completing, and presenting a capstone project.

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Chapter 4: Institutional Considerations
4.1. Evolution and Status of Computing Degree Programs
Most academic institutions face important decisions about the best way to evolve their computing degree
programs. However, not all colleges and universities face the same set of challenges. Fortunately, we
can characterize a small number of program attributes in such a way that people at the great majority of
North American colleges and universities will be able to recognize their circumstances within these
parameters. We now characterize the institutional attributes, taking each computing discipline in turn.
Computer Engineering. Very few institutions face a dilemma about whether to offer a CE program. For
institutions that have a School of Engineering (or analogous unit), a CE program almost certainly exists
already in some guise. Most often, it is in the form of an explicit CE program, though some institutions
provide the same concentration in the form of a combined effort of their CS and EE programs. As of
mid-2004, approximately 500 programs exist in computer engineering in the U.S., and thousands more
exist elsewhere. A North American institution that does not have an engineering program is not likely to
succeed at creating an accredited CE program since accreditation requirements are difficult to meet
without a substantial supporting administrative structure.
Computer Science. Very few institutions face a dilemma about whether to offer a CS program simply
because virtually all colleges and universities already have one. CS is by far the most ubiquitous of
computing degree programs. The most common scenario is that computer science grew out of a
mathematics department in the 1970s. Frequently, that department morphed into a Mathematics and
Computer Science department for a decade or two before splitting apart into separate departments for
mathematics and CS in the 1990s, though a considerable number of Mathematics and Computer Science
departments remain today. At universities that had an electrical engineering program, it was common for
CS to grow out of the electrical engineering or math department or both. While these scenarios are most
common, alternative scenarios abound. During the 1990s, a small number of institutions recognized the
pervasive influence of computing by creating an autonomous unit such as a school or college of
computing, a move that showed both insight and foresight. Regardless of where the institution placed the
program, most saw their CS programs struggle for local academic legitimacy in the 1970s and 80s, then
emerge as established and prominent programs during the 1990s. At most institutions, the CS program is
(or should be) facing serious choices about two closely related issues: (1) the appropriateness of a narrow
CS identity in light of the issues discussed in Section 3.2, and (2) how to best respond to the emergence
of newer computing disciplines, also in light of Section 3.2 issues.
Information Systems. As of mid-2005, there are about 1000 IS programs in the U.S., although they use a
wide variety of names such as information systems, management information systems and computer
information systems. Hundreds of IS programs exist elsewhere in the world, again with a variety of
names. Like computer science, the early programs appeared in the 1960s, with most appearing in the
1970s and 1980s. Also like CS programs, IS programs now face fresh competition from IT programs.
Faculty at some IS programs are happy to see new IT programs take responsibility for areas that were of
little interest to them; others fear the loss of influence and turf. Regardless of the local IS reaction to the
emergence of IT programs, there are many potentially rich opportunities for cooperation between the IS
and IT communities.
Information Technology. As of mid-2005, about 70 American institutions have IT degree programs.
Because of the rapid growth of such programs, it is difficult to know how many currently exist. Many of
the existing programs are truly in the vanguard: they are high quality programs that have been forging
ahead into uncharted territory, creating new offerings tailored to the special needs of this emerging field.
Unfortunately, some IT programs are of low quality and fail to serve either their students or their

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communities in a responsible way. The latter group of programs seeks to increase enrollments and/or
provide the image of being responsive to local needs by creating an IT program that is little more than the
repackaging of existing courses offered in other disciplines. Most institutions don’t yet have an IT
program, but many are in the process of deciding whether to start one. Those who choose to do so should
take special care to ensure that they are following the leadership example of the high-quality IT programs,
not the exploitive example of low-quality programs. A powerful driver that has led to the development of
the upcoming IT2005 curriculum volume is the desire to provide substantive guidance for those trying to
develop high-quality IT programs.
For those who are considering an IT program a key question is, “Does the IT agenda fit with the
institution’s mission?” Opting to create an IT program implies a decision to respond to community needs
for well-prepared IT practitioners by creating an overtly career-oriented program. This differs from the
traditional academic focus of programs in the arts and sciences and thus implies some basic questions.
What is the institution’s mission? Is it local, regional, or national in scope? What responsibility, if any,
does the institution have to meet local and regional needs?
Software Engineering. As of mid-2005, more than 30 American institutions have dedicated SE degree
programs (far fewer than exist in the U.K. and Australia). Many of these are vanguard programs that
have recognized the need to prepare students for creating large and/or safety-critical software. Their
educational program focuses student preparation on these needs more completely than CS and CE
programs can be expected to do. We expect the number of SE programs to increase, although not at the
same rate of growth we expect to see in IT programs. SE programs provide an opportunity for an
institution to distinguish itself in ways that directly addresses academic and professional challenges.
Some U.S. institutions that offer an SE degree program may opt to use a degree title that does not include
the word engineering. In North America, conflicts can arise when the word engineering is used in the
name of a degree program that is housed outside an engineering college. As a result, we expect some
high quality programs to use another title. In some cases, SE-like programs will take the form of a
standalone degree program. In other cases, they may exist as an especially substantive concentration
within a CS degree program. The content of the program, not the label on the degree, determines whether
it provides high-quality SE education in the sense described in this document.
For institutions considering a SE program, a key question is, “Does SE warrant a dedicated program?”
This implies a local consensus about whether the CS agenda provides students with sufficient preparation
for a career as a professional software engineer. If the local consensus sees the need for an explicit SE
program, and if adequately qualified faculty members are available, the question becomes one of
implementation structure. Should it be handled as one of several optional concentrations within CS? Or
does it imply programmatic differences in terms of structure and requirements?

4.2. The Portfolio Strategy
The increased diversity of computing degree programs presents important challenges and opportunities.
Computing educators face more choices and tougher decisions. Being responsive implies adaptation and
change and, by their nature, institutions find it hard to adapt and change.
While fiscal constraints provide a justification for dismissing the prospect of revising or initiating
computing degree programs, inaction can have its own consequences. The new diversity of computing
programs gives institutions an unprecedented opportunity to focus their degree programs to meet the
needs of their students, communities, and other constituents in the most effective way. It allows
educational institutions to demonstrate initiative, foresight, and responsiveness in very tangible ways.
One of the great potentials of the new diversity of computing degree programs is that it permits academia
to bring its computing degree programs into line with the diverse needs that exist among students and in

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local communities. In the past, many institutions had little choice but to have a CS program on the
technical side and perhaps an IS program on the business side. Now a college might offer a portfolio of
degree programs to serve various student needs more appropriately such as:
• a CS program to serve those students who wish to proceed as generalists in computing or who aspire
to graduate study, research positions, or cross-disciplinary innovation;
• an SE program to serve students who have the intellectual and technical aptitude to excel as software
developers and who want to become expert at developing large scale software, working in teams and
producing robust products that meet customer needs;
• an IT program to serve students who want a computing career that features a mix of technical and
people issues rather than a unilateral focus on technology and who are attracted to the widespread
need for IT professionals in a variety of organizations and settings;
• an IS program in cooperation with other business programs to serve students who want a career that
focuses on the information needs of organizations and who are interested in technology primarily as a
vehicle to meet such needs; and
• at those universities that have an engineering program, a CE program to serve students who want a
career that is focused on developing computer-based devices.
Diversity and diversify have the same root, and recent patterns of computing enrollments suggest that a
diversification strategy, useful in insulating one’s investments from erratic swings in value, may be
similarly useful in protecting an institution’s computing programs from unpredictable enrollment swings.
Recent events provide a timely illustration. CS programs have long seen cyclical enrollment patterns. In
recent years, the dot-com boom saw unprecedented CS enrollments. When that bubble burst, CS
enrollments plunged. More recently, when the expectation was to see a gradual return to rising CS
enrollments, many programs have seen just the opposite, further declines in CS enrollments. These facts
do not mean that computing degree programs are less popular. In the face of widespread reports of falling
enrollments in CS, various institutions report that their SE enrollments remained steady and that IT
enrollments continued to increase. Some institutions that provide IT and SE programs in addition to a CS
program are not reporting big downturns in aggregate computing-degree enrollments but instead are
reporting net increases in computing enrollments despite CS decreases.
Such evidence is purely anecdotal. Many factors may be in play, and hard evidence is not readily
available. However, such anecdotal reports provide interesting food for thought. There is good reason to
suspect that a portfolio strategy might help institutions better meet the needs of their students.
• To the extent that a given institution’s student population presents a range of interests and sets of
abilities, a broader range of computing degree choices might permit the institution to do a better job of
serving that range of students needs.
• At many institutions, student retention is an important concern. Colleges and universities routinely
report that 50% or more of those students who initially choose CS study soon decide to abandon it. It
seems plausible to expect that the better the match between student interests and abilities and available
degree programs, the better the retention level that can be achieved.
• Apart from retention, computing educators (and others) have long been concerned with the relatively
narrow profile of students who are attracted to the computing disciplines. A broader portfolio may
prove to attract a wider population. For example, some institutions that offer IT programs report
increased participation by women and minorities but, again, the evidence is anecdotal.
• When an academic unit offers a family of quality computing degree programs, its faculty will naturally
come to reflect a variety of perspectives on computing issues and challenges. This kind of situation can

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set the stage for a useful cross-fertilization of ideas among the disciplines which might, in turn, support
creativity and innovation in both teaching and research.
Many academics are asking themselves about program diversification quite explicitly: “What portfolio of
computing degree programs should we be offering?” This implies an important educational question that
was rarely asked before the emergence of the new computing disciplines: “What kinds of computing
education best serves our students and community?” The portfolio question also requires that decision-
makers weigh the benefits against the costs. Obvious costs include the initial costs of creating new
programs as well as the ongoing overhead of administering multiple programs.
How do the potential benefits and costs compare? There is no standard answer, and each institution must
make a decision in light of its own mission and circumstances. For some institutions, the answer will be
easy, while others will face difficult choices. The key question is clear: “What options best serve our
students, our community, and our future?” Even institutions facing resource constraints that preclude
immediate program initiatives can gather key people to consider this important question.
Any serious consideration of program diversification is likely to see certain issues arise. In the next
section, we discuss key factors that will likely come into play.

4.3. Institutional Challenges to Diversity
For any college or university trying to come to terms with the new diversity of computing degree
programs, there are at least three areas in which effective leadership and a willingness to change are
necessary. These areas are faculty development and adaptation, organizational structure, and curricular
structure. Each of these areas involves issues that, by their nature, invite polarities of opinion among
faculty. As is often the case when issues elicit strong differences of opinion, there are implicit value
choices that underlie the explicit issues. Any honest and thorough planning effort concerning an
institution’s computing degree programs should not only face these issues themselves but should also
examine the fundamental value choices that underlie differences of opinion in each of these three areas.
4.3.1. Faculty Development and Adaptation
When an institution that currently offers a CS degree decides to diversify by expanding its mission to
include SE and/or IT programs, it is likely that some difficulty will arise with respect to finding
appropriate faculty. After all, for most institutions, CS faculty is the only available computing faculty.
Most of the faculty members will naturally be oriented to the CS mission that shaped their own
professional growth and development. Suggesting that they broaden their mission to fully encompass the
SE and/or IT agenda is likely to produce a mixed reaction along each of the following lines.
• Legitimacy. Some CS faculty will have the view that SE and/or IT have not yet developed to the stage
where they can be considered as academic disciplines. Some will argue that SE deserves a course or
two within the context of a CS major but does not warrant or require a distinct programmatic focus.
Some will argue that IT offers an agenda that is too vocational. Other CS faculty will be more aware
of the important social functions provided by each of the scientific (CS), engineering (SE), and
practitioner (IT) professions, and therefore will be more inclined to see a need to broaden the
computing education agenda. The latter group can play a valuable role in persuading a skeptical
faculty of the validity and importance of the engineering perspective that is central to SE and the
practitioner perspective that is central to IT.
• Preparedness. Most CS faculty will not have the necessary background to immediately teach courses
that substantially differentiate SE and IT from CS. This is a natural consequence of the fact that their
background is in CS rather than SE or IT. It is important that these issues are not swept under the
carpet as faculty shortcomings can be disguised to the detriment of all. This risk is especially present

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because CS faculty will be knowledgeable about most computing topics but with a CS orientation that
falls short of the needs of SE and/or IT students. For example, both CS and IT students need to know
about computer networks. Much of the material is equally important to both CS and IT but, after a
point, the agenda splits: CS will emphasize underlying models and principles, while IT will emphasize
practical application skills related to network management and security. In practice, most CS faculty
have never managed a network or been responsible for maintaining network security. Similarly, most
CS faculty will be able to teach a CS course about SE but have not had occasion to obtain the
knowledge and experience to teach a full-fledged SE agenda that helps students become software
engineers. Care must be taken in at least two dimensions.
1. A CS treatment of shared topics masquerading as SE or IT coursework is quite inappropriate;
2. If CS faculty members are to develop the ability to teach SE and IT courses, it is necessary that they
be provided substantial resources to help them prepare and adapt to the very different agendas implied
by the engineering and practitioner perspectives.
With respect to both legitimacy and preparedness, the core challenge is to enlist faculty support for new
programs and to respond by providing faculty with the support they will require. A high-level decision
for a broader computing agenda may well be necessary, but it is unlikely to be sufficient. Some faculty
members will be more adaptable and more willing to embrace the challenges presented. Successful
efforts will identify faculty who want to develop new capabilities and then provide support for them in
order to undertake the kind of self-education and preparation that is needed for them to succeed.
4.3.2. Organizational Structure
Diversification presents choices about how and where computing degree programs should be housed.
Should each discipline have its own department? Should they all reside within a single multifaceted unit,
such as a Department of Computing? Is it best to bypass traditional departmental structures altogether
and create a center to house new programs? There are proponents for each approach. There is no
compelling answer as to which is best, and each institution must consider its own context and mission.
Each of the computing disciplines features a distinct character and focus. At the same time, their teaching
and learning agendas are far from distinct as many topics and skills are relevant across the various kinds
of degree programs. This fact creates a natural tension between the advantages of having distinct,
separate departments and the advantages of offering different degrees from within a single computing
department. The former approach makes it easier to ensure that each degree program is free to do its job
properly without significant compromise. The latter approach may make it easier to leverage
commonalities among the disciplines so that economies of scale can replace redundancy in curricula,
computer labs, teaching loads, etc.
Those contemplating structural changes should be aware that we expect change and innovation to be
ongoing. While SE and IT degree programs are relatively new phenomena, they won’t be the last word in
new computing degree programs. As institutional leaders answer the question of “What to do with SE
and/or IT?”, they should also ask themselves what they might do with the next new kind of computing-
related program whatever it might be. If a new organizational structure is being created, what is its
purpose: to solve the immediate dilemma or set the stage for the long run?
4.3.3. Curricular Structure
Regardless of whether computing degree programs are housed in the same academic unit or in different
departments, the commonality that exists across the computing disciplines invites questions about the role
and purpose of various courses especially introductory courses. Two related issues naturally arise.
• Filter vs. funnel approaches. At the introductory level, there are two basic philosophies to course
targeting which can be described as filter and funnel. The filter approach calls for curricula that

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implement an ambitious, tightly focused discipline-specific agenda from the very first course. Filter
curricula use introductory courses to lay disciplinary foundations early and/or establish a rigorous
performance standard from the beginning to immediately filter out students who don’t rise to the
standard. In contrast, the funnel approach calls for curricula that serve a student audience that is
broader than those who will concentrate and succeed in a given discipline. Funnel curricula use
introductory courses to provide students with learning experiences that will help them make a well-
informed choice as to whether a given discipline is suitable for them.
The filter approach calls for parallel discipline-specific introductory course sequences, one for each
computing discipline. The main motivation for the filter approach is rooted in factors that leave faculty
with what they feel is insufficient time to provide students with necessary preparation for their chosen
field. Filter proponents generally believe that their program must establish a strong disciplinary
foundation early and therefore cannot afford a common introductory course for all computing
disciplines. Alternatively, the institutional context (such as traditional engineering for CE and business
for IS) may dictate a curriculum framework that leaves little or no room for a common computing
introduction. In addition, some proponents of the filter approach argue for parallel curricula on the
grounds that students can be best challenged if they are segmented as soon as possible. According to
this view, not only do you want parallel introductory sequences, one for each audience, but you also
want the early courses to serve as filters that keep students from following a course of study for which
they do not initially show high aptitude. Thus, we find different opinions among filter proponents:
some think the filter approach is unfortunate but necessary, while others believe it is preferable on its
merits. Regardless of motivation and rationale, filter proponents argue that students can and must make
an appropriate choice of degree program at a very early stage of their undergraduate career, often
before they have any coursework or other experience related to the discipline they are choosing.
For filter curricula to serve students responsibly, degree program must provide students with some
reasonable and substantive support for making an informed choice about the degree program, and this
must be done before the student enters the program. It is neither reasonable nor responsible to expect
young people to make important, life-shaping decisions based primarily on the names of degree
programs and the names of introductory courses. While active, effective means of advising students is
always valuable, it is especially important for a curriculum that features a filter approach.
Proponents of the funnel approach argue for a common introductory sequence, contending that most
students cannot be expected to have clarity about their choice of major as a freshman and that the best
way for students to obtain clarity is through course experiences designed to give them a feel for the
computing disciplines. According to this approach, not only do you want an integrated introductory
sequence, you need one if you want students to make well-informed choices among degree programs.
In the U.K., a shared first year of introductory computing courses is very common; experience there
has shown that delaying the decision about choice of major can be beneficial in helping with retention.
Another motivation for having shared courses is the high cost of maintaining distinct sets of courses for
each degree program. In addition to a reduction in course maintenance costs, reducing the number of
courses that must be maintained makes the challenge of keeping each course optimized more tractable.
While all funnel approaches bring a broad population of students through an introductory experience,
funnel designs can differ in what happens after that. One design may have students choose from
several computing degree programs. Another design might give students the sole choice of continuing
in a single computing discipline (often computer science in the U.S.) or abandoning their computing
studies. In either case, the introductory experience helps students make well-informed decisions; what
varies is the number of computing degree programs about which they can make an informed decision.

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The funnel approach can present some important challenges, depending on its scope. A funnel
approach is easier to design if it is targeted at only a single discipline, for example, a CS program that
uses its introductory courses to serve a broad campus-wide audience. In this scenario, undecided
students can get a rigorous introduction to programming fundamentals, while simultaneously getting a
feel for whether they wish to pursue further CS study. In this case, the funnel courses are targeted to
serve a single degree program so it is easier to know how to best focus the material.
Curriculum integration across multiple computing degree programs presents faculty with a more
challenging design problem. The goal is to give students direct experience with the kind of work that is
featured in advanced courses from various computing disciplines. This can give students the best
possible basis for making a decision from the available computing degree programs, but it requires that
those who devise and implement such courses think outside the box and be sensitive to the needs of
each of the computing disciplines especially those other than their own. The worst possible scenario is
that one computing discipline will hijack the introductory sequence to serve its students, creating a
filter that directs those who don’t succeed in that preferred discipline to one of the other disciplines.
We know of no curriculum model that provides a successful funnel approach that serves all five
computing disciplines. However, faculty at various schools, including many U.K. universities, report
success with funnel courses that serve two or three disciplines. The absence of solid models that serve
all five disciplines is likely a reflection of two factors: the inherent difficulty implied in the task, and
the simple fact that few schools have much experience as yet in providing degrees in all five
disciplines. We expect that future generations of the various discipline-specific curriculum guidelines
will investigate and assess introductory models that have demonstrated success at serving a broad
funnel agenda.
• Granularity of curriculum components. While many of the topics and skills relevant across the various
kinds of degree programs are found in the first year or two of study, commonalities extend throughout
the entire degree program. For example, programs in each of the computing disciplines need to have
advanced courses about operating systems, networks, databases, and other areas. For each such area,
some material is appropriate to students of all the disciplines, while other coverage requires a
discipline-specific treatment. While the commonalities are numerous, they cluster in chunks that are
considerably smaller than a traditional semester course and, as a result, fall through the cracks of
traditional course designs. This can cause each degree program to have its own custom course despite
the fact that its course has much in common with similar courses for other computing majors.
Reason suggests that there may be great opportunities in devising courses of shorter duration that can
be combined as appropriate for the different disciplines. One can imagine a handful of short (perhaps a
few weeks duration) modular courses on various aspects of networking such that, for example, CS
students might have some modules in common with IT students, with other modules focusing explicitly
on what is unique to the CS or IT agendas. This approach offers obvious potential benefits but also
presents various local logistical challenges. While this is seemingly a sound idea, considerable
experience is required before we can judge its utility.
Because the diversity of computing programs is new, we have little collective experience in sorting out
these issues. Hence, there is great need for innovation and experimentation. Many who favor the funnel
approach to curricula feel that the most pressing need is for a new model of introductory courses that can
differentially direct students to the right degree program. The challenge is to develop a sequence that is
neither preferential nor pejorative to any discipline but instead gives students knowledge and experience
that foreshadow what they will see and do in each computing degree program. Developing such a
sequence seems an important challenge, one that is likely to involve new insights into what is common
throughout computing in addition to programming. To date, we do not yet have a compelling model for

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how to achieve this successfully. We hope to see educators make progress in this area over the next few
years as successful models will provide compelling benefits to students and institutions alike.

4.4. Academic Integrity and Market Forces
Market forces impact academic programs in various ways, some of which are beyond the scope of this
report. For example, in recent years various forms of certification have become popular. The term
certification applies to a wide range of offerings that vary in important ways. Some certifications are
vendor-specific (e.g., those from Microsoft, Cisco, etc.). Other certifications are available through
professional organizations (e.g., IEEE-CS, BCS) and other organizations (e.g., ICCP). In some of its
forms, certification competes with academic programs. It is clear that certification is a major trend. As
with anything else, some certifications are respected, while others are controversial. When degree-
granting institutions partner with vendor-specific certification programs, academic integrity becomes an
issue. The reader should be aware that such partnerships invite controversy about academic integrity and
ethics. It is beyond the scope of this report to address issues related to the broad range of certifications.
As certification is addressed by other project reports, we will reference such work in updated versions of
this report. Our focus is limited to undergraduate computing degree programs.
The fact that we see new kinds of computing degree programs emerging to address social needs shows
that the dynamism of our society is not lost in academia. The newer computing disciplines provide proof-
by-example that academia can and will evolve and be responsive to social needs. Sadly, that same
emergence of new degree programs also provides examples of what can go wrong when academic
initiatives are driven by political agendas, fiscal imperatives, and media hype rather than by recognition
that substantive innovation is needed to address important concerns.
Fortunately, it is easy to distinguish between these two kinds of phenomena. When we look at the
emergence of new computing degree programs, we see examples of both high- and low-quality programs.
• When we look at high-quality programs, we see coherent programs that are driven and developed from
within. Faculty and local administrators contribute because they have looked beyond the boundaries of
conventional subject-matter areas, recognized that their students and their community need something
new and different, and innovated to solve what they see as a legitimate, substantive problem. The
faculty in such programs tends to identify itself as the faculty of the new discipline, despite the fact that
it’s background is invariably in another discipline. Faculty members value their students, see student
and community needs as legitimate, and strive to hold students to high standards appropriate to the
discipline.
• When we look at low-quality programs, we see programs that are driven from without. One scenario
involves a top-down process wherein someone in power decrees that new programs will be created,
perhaps to fit an arbitrary timeline. Faculty and administrators contribute because they are told to do
so. They do not see intrinsic positive value in the initiative; they do not see it addressing legitimate
needs of students or the community. Hence, they innovate to provide the superficial appearance of
innovation, often by creating new programs that are nothing but collections of existing courses from
other departments. Faculty members involved in such programs tend to identify themselves as faculty
in the older, more established discipline from whence they came.
An important lesson here is that good programs do not emerge on the basis of top-down directives alone.
While a top-down directive may be a necessary catalyst, good programs require care and nurture from
faculty who can and do see opportunities to do work that has important potential and inherent legitimacy.
While fiscal pressures can make creating programs to meet demand an attractive option, academic
integrity requires more than just a superficial response to market forces. It is critical that creation of new
computing programs is treated as a substantive development effort, undertaken by people who care and
who are supported with resources sufficient to permit the development of substantive, coherent programs.

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4.5. Accreditation and Computing Curricula
Academic accreditation is a process that is used to support improvement of institutions and their degree
programs, to demonstrate that a degree program meets certain external requirements, and to increase the
level of confidence the public has in them.
In some countries, accreditation can occur at different levels of an academic institution. In these cases,
institution-wide accreditations certify that a university meets minimum standards for resources (e.g.,
library) and operating procedures (e.g., admissions policies) required of any legitimate institution of
higher learning. Similar guidelines may exist for an entity within the institution (e.g. a business school)
that encompasses degree programs in related fields. Accreditation for a school that houses a group of
programs is similar to institutional accreditation but with greater specificity.
The most stringent form of accreditation concerns the evaluation of individual degree programs. This
involves the participation of independent organizations or government agencies that establish quality
standards and criteria for degree programs in a specific discipline. Discipline-specific (or program)
accreditation involves an evaluation of specific degree programs and certifies that a degree program meets
established criteria and has rigorous processes for ongoing improvement. Accreditation does not exist for
every discipline, but it does exist for computing degree programs.
In nations where accreditation can occur at different levels, an institution may be accredited by an
organization that accredits universities, while its computing degree programs may not be accredited by
the body that evaluates the quality of computing degree programs. For example, a U.S. university may
have unaccredited degree programs even though the university as a whole is accredited. The distinction
to keep in mind is that the accreditation of a college or university does not imply that its computing degree
programs meet the standards of quality established for the computing disciplines.
4.5.1. Benefits of Discipline-Specific Accreditation
Discipline-specific accreditation provides two important benefits for programs and for the institutions in
which they reside.
1) It certifies that a degree program meets minimum quality standards established by independent
professional or scientific societies or by government agencies. This helps an institution market its
programs, and it gives the public and prospective students reason to be confident in a particular
degree program’s quality.
2) The program receives an onsite consultation by a visiting team that provides an expert opinion about
a program’s strengths and weaknesses and about its specific needs for improvement. This interaction
helps an institution have full understanding of how its programs are performing and what must be
done to improve their quality.
Thus, accreditation provides the benefits of both a marketing aid for attracting students and an expert
consultation focused on improving quality. Some institutions may not need or desire the former benefit.
Of these, some are committed to accreditation solely because the accreditation process helps them
maintain and improve the quality of their programs which, in turn, further cements their reputation. In
some nations, institutions have no choice because accreditation is a requirement for program existence.
Discipline-specific accreditation processes determine whether a candidate degree program meets certain
criteria. Not only does accreditation determine whether the program provides sufficient qualified teachers
with acceptable workloads, it also determines how the program uses materials and assignments, evaluates
assignments and examinations, and engages itself in continuous evaluation and improvement.
Professional bodies also use this accreditation to ensure that degree programs meet, at least in part, the
requirements for membership in their profession. In some cases, graduation from an accredited degree
program is a requirement for individuals before they can practice in a particular profession. This means

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that it is not sufficient for a student who wishes to practice a profession simply to earn a degree in the
appropriate discipline; rather, he or she must have earned that degree from an accredited degree program.
A given degree program does not choose whether its accreditation has such professional elements; its
accreditation process is determined by what is customary for its discipline in its nation. For example, in
the U.S., accreditation for engineering programs includes professional aspects, those for other kinds of
degree programs often do not, and most arts and sciences disciplines do not have accreditation at all.
Perhaps the greatest misconception about accreditation is the belief that institutions pursue program
accreditation only to obtain a stamp of approval. Those unfamiliar with discipline-specific accreditation
often do not understand the important role that the accreditation process plays in helping a program know
exactly what it must do to improve the quality of both its offerings and its graduates.
4.5.2. Accreditation and Quality
Discipline-specific accreditation is a means of demonstrating that a degree program meets an independent
standard of quality, but the meaning of that standard varies. Its rigor is determined by the accrediting
body’s policies and practices and by any government regulations that might apply. In some cases,
accreditation certifies that a degree program has met a minimum quality standard. In other cases, there
exist both minimum standards and higher standards.
While discipline-specific accreditation is concerned with program quality, it is important not to reach
unwarranted conclusions about the relationship between accreditation and quality. One must be familiar
with both the discipline and the national context in order to reach appropriate conclusions.
DOES THE ABSENCE OF ACCREDITATION INDICATE THAT A PROGRAM IS OF LOW QUALITY?
The answer depends on the discipline and on the national context. For example, most U.K. computing
programs are accredited (see Section 4.5.4). The situation in the U.S. is much more varied: while every
reputable CE program is accredited, most CS programs are not accredited, and accreditation of IS, IT, and
SE programs is only now beginning (see Section 4.5.5).
DOES THE FACT THAT A PROGRAM IS ACCREDITED INDICATE THAT IT IS OF HIGH QUALITY?
The answer depends on national context. In some nations, accreditation indicates only that a program has
met a standard of minimum acceptable quality; in others, accreditation recognizes different quality levels.
DO ALL ACCREDITATION PROCESSES INVOLVE THE SAME PROCEDURES?
No. There are important differences in quality assurance practices between nations. For example, in the
U.S., an accreditation team must review and assess a program at all its levels from specific class
assignments to high-level programmatic issues as part of the accreditation visit. In contrast, U.K. quality
assurance practices include the involvement of external examiners as part of daily operations. In the
British system, all class assignments and examinations and their evaluation criteria are reviewed and
evaluated in advance by faculty from other institutions. This means that students in British classes never
receive an assignment or an examination that was prepared spontaneously or that lacks appropriate
evaluation criteria. If an assignment or its evaluation criteria does not satisfy the external examiner, it
must be improved until it does. While these quality assurance practices are unrelated to accreditation, the
written evaluations produced by external examiners are available to the accreditation team. This provides
the accreditation team with evaluation data obtained over time, freeing the accreditation team from
studying low-level details and permitting them to focus on quality issues at a higher programmatic level.
APART FROM ACCREDITATION, WHAT ARE SOME INDICATIONS OF HIGH- AND LOW- PROGRAM QUALITY?
There are several aspects of high quality: good teachers, a workload that permits teachers to focus
adequately on their classes and remain current in their field, sufficient infrastructure, and so on. One of

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the most important things to look for is evidence of rigorous procedures for monitoring and improving
quality in an ongoing way. It is important that adequate processes be in place to recognize where
improvements are needed and that information about quality is actually used to produce demonstrable
improvement.
In a good program, quality monitoring processes are integrated with initiatives for improving quality to
form a continuous cycle: each improvement effort is monitored for effect, new improvement efforts are
then planned and implemented, the results evaluated, and the cycle repeats. Doing this properly is not
difficult, but a measure of commitment, discipline, and information sharing and use are required.
It is difficult for someone who is not privy to the internal operations of a degree program to know what
actually occurs. In terms of more accessible features, one should inquire about items such as:
• a professional advisory board: Is there one? Who is on it? Does it focus on educational aspects of the
program, or is it concerned only with a department’s research program?
• the use of information obtained from students: Does the program do more than collect data from end-
of-term student satisfaction surveys? Are students involved in various academic committees? Does the
program use exit interviews to get the opinions of graduating students about the program’s strengths
and weaknesses? Are graduates of the program consulted after they work in industry for a few years?
Does evidence exist that such information is used in ways that lead to demonstrable improvement?
• the processes for systemic evaluation and improvement: Are procedures in place to evaluate the
effectiveness of each course? What methods are deployed to assess the strengths and weaknesses of a
program’s graduating students? What processes ensure that such information is actually utilized?
Meaningful quality improvement requires more than simply calculating student grade point averages and
collecting data from end-of-term student satisfaction surveys. If a program has little to point to beyond
collection of these basic data, it is reasonable to have doubts about whether there is an adequate focus on
systematically improving the quality of both the degree program itself, and of the graduates it produces.
4.5.3. National Traits and International Cooperation
Many countries have embraced accreditation. The details vary but there is a common thread: a panel of
experts who represent a profession evaluates a program’s quality against established standards and
criteria.
Nations vary with respect to whether accreditation is mandatory, strongly encouraged, or voluntary.
Some countries have rigorous program criteria and require that accreditation standards apply to every
program offered at any college or university. In other countries, accreditation is voluntary. Among
countries in which accreditation is voluntary, the extent to which accreditation is expected differs.
The administration of the accreditation process also varies. In some countries (e.g., Australia, Canada,
and the U.K.) professional societies conduct program accreditation for their respective fields. In other
countries (e.g., the U.S.) a designated organization monitors and/or performs accreditation. In some
countries (e.g. Estonia and the United Arab Emirates), the government conducts the accreditation process.
In some computing disciplines, accreditation agencies also cooperate across national borders. For
example, in addition to its accreditation activities in the U.S., ABET has assisted other nations in the
evaluation of their programs for more than 20 years. Mutual recognition of evaluation and accreditation
processes has encouraged a range of international agreements such as the Washington Accord, the Sydney
Accord, the Dublin Accord, the European Federation of National Engineering Associations (FEANI), and
the International Register of Professional Engineers (IRPE). Such agreements have a range of signatories
but they share a common goal, that is, to facilitate the movement of professionals across nations. For
example, the Washington Accord is an agreement among the organizations that accredit engineering

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degree programs in Australia, Canada, Hong Kong, Ireland, Japan, New Zealand, South Africa, U.K., and
U.S.; it recognizes the substantial equivalence of programs accredited by these bodies.
4.5.4. Computing Accreditation in the United Kingdom
The U.K. Engineering Council (ECUK) is responsible for accreditation of engineering degree programs.
Its responsibilities include setting standards (of competence and commitment) for the accreditation of
engineering degrees and approving nominating bodies that carry out detailed accreditation on its behalf.
The British Computer Society (BCS), on behalf of the Engineering Council, carries out accreditation of
Information Systems Engineering degree programs that encompasses most of what falls into the
computing field. The Institute of Electrical Engineers (IEE) carries out the accreditation of electrical
engineering degree programs. Degree programs in computer engineering could be accredited by either
society, though perhaps more often by IEE. Joint accreditation by both societies is common.
In addition, the U.K. government has instituted its own quality assurance procedures for all disciplines,
using the Quality Assurance Agency (QAA). The QAA is responsible for benchmarking degrees. Each
institution is required to demonstrate that their degrees meet the benchmark standards for that discipline.
One example of these benchmark standards is UKQAA 2000 which defines both threshold (minimal) and
modal (average) expectations with respect to demonstrated student knowledge, skills, and judgment.
4.5.5. Computing Accreditation in the United States
Until recently, computing accreditation in the U.S. was limited and fragmented. It is now more unified
and more extensive. Historically, two organizations accredited computing degree programs. The
Accreditation Board for Engineering and Technology (commonly know as ABET) accredited
undergraduate engineering programs of all kinds, including electrical engineering and computer
engineering. The Computing Sciences Accreditation Board (known as CSAB) accredited undergraduate
computer science programs. Recently, CSAB, recreated as CSAB Inc., has become a member society of
a renamed ABET Inc., and now ABET accredits engineering, technology, computing, and applied science
programs. Currently, accreditation of CE, CS, IS, and SE programs is ongoing, and accreditation of IT
programs has begun.
Accreditation in the U.S. is voluntary in the sense that no law or regulation requires a degree program to
be accredited. As a practical matter, it is more voluntary in some computing disciplines than in others. In
engineering, for example, a strong sense of a professional community exists and state-regulated licensing
of engineers can require applicants to hold an engineering degree from an ABET accredited program. As
a result, we expect accreditation status for all CE programs, and any CE programs that are not accredited
are unlikely to be credible. The situation is less clear for SE programs because SE is new and, by its
nature, has far fewer ties to traditional engineering.
In contrast, the CS community is more of a loosely organized network of scientists, researchers, and
programmers than a tightly organized body of practicing professionals. Historically, there has been no
compelling professional pressure for accreditation of CS programs; demand comes from universities
seeking accreditation. Currently, less than ten percent of U.S. CS programs are accredited, while nearly
all of U.K. computing programs are accredited. Recently, however, demand for CS accreditation has
increased. The IS discipline is often associated with schools of business that have their own tradition of
accreditation. The IT discipline is new, and because most IT professionals are primarily concerned with
technical competence, it would not be surprising to see IT programs seeking accreditation.
The philosophy of ABET accreditation has recently shifted from prescriptive criteria to outcome-based
approaches. The new approaches require each program to define its objectives and demonstrate that its
processes ensure that it is achieving those objectives.

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Chapter 5: Next Steps
This list summarizes curriculum-related developments that are planned for the near future.
• Publication of the IT2006 report.
The current draft is available for review and comment at http://www.acm.org/education/curricula.html.
Publication of the final version is expected in 2006.
• Publication of The Guide to Undergraduate Degree Programs in Computing.
The Guide will be a smaller companion report to the Overview Report. It will be aimed at a broader
audience, including prospective students, their parents and guidance counselors, and others who have
reason to care about the choices that await students who move from high school to college. It will
provide brief characterizations of the computing disciplines, profile factors that prospective students
may consider when choosing an area of computing study, and will be widely distributed as an
independent document. The Joint Task Force plans to present drafts for public review and comment
early in 2006 and to have a final version ready for publication by mid-2006.
• Implementation of new timetables for revision to each volume in the Computing Curricula Series.
In the past, not only were curriculum reports limited to a much smaller range of computing disciplines,
but those guidelines were revised only about once every 10-to-12 years. Given the rapid pace of
change in computing, more frequent revisions are required. The long-term goal is the development of
processes that will permit us to issue revisions as needed, driven by evolution in subject matter.
While we develop appropriate processes (see the following), as an initial approximation of an
appropriate schedule, we intend to cut the previous cycle in half with revisions to each of the
discipline-specific volumes appearing every 5-to-6 years instead of every 10-to-12 years. Thus, a task
force will be formed in mid-2005 to update the computer science volume (generating what will become
CS2007), followed by a task force to update IS2002 (generating IS2007 or IS2008). Whenever an
updated discipline-specific volume is published, an updated version of this Overview volume will
follow it.
• Initiation of new processes for capturing feedback about each volume in the Computing Curricula
Series (including the CE, CS, IS, IT, SE, and Overview volumes) in an ongoing way.
In the past, opportunities for members of the computing community to provide input and feedback
concerning curriculum recommendations were limited. Beginning with the SE2004 volume, and
continuing with this volume and the IT2006 project, we have begun to provide opportunities for
anyone, anywhere to submit suggestions and critiques via online tools. We intend to refine the tools,
improve their visibility to the larger computing community, and make them consistently available. The
goal is to permit motivated people to provide the benefit of their experience and opinion throughout the
life of each report rather than only during an explicit report development effort.
• Fueled in part by such feedback, new processes for ongoing evaluation of the adequacy of each volume
in the Computing Curricula Series, including processes for specifying needed changes to each volume.
It is clear that curriculum reports must be updated more frequently than once per decade, but we do not
want to issue updated volumes in an arbitrary fashion. New volumes call for change at the local level,
and each set of changes imply costs. In an ideal world, new volumes would be issued in response to
some critical mass of change and evolution in the field, driven by need rather than by a schedule. For
this to occur, we require processes that permit us to monitor evolution in the field, identify specific
needs for curriculum revision, and issue revisions as needed. The societies that cooperated on the
creation of these volumes are in the process of creating a task force to address this important issue.

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• Improved support for frequent updating of curricula.
Not only must we develop capabilities for updating each volume as needed, we also require effective
ways of looking across the various volumes. Our current practices imply relatively independent efforts
for each discipline-specific volume which is very labor intensive. At the same time, changes in
computing often apply across disciplinary boundaries. The Computing Ontology Project is currently
developing a framework for modeling all computing subject matter across the computing disciplines.
The goal is to produce both schema and tools that will permit us to see the superset of computing’s
problem space, update the particulars in that shared space in response to ongoing developments in
computing, identify which disciplines are affected by those developments, and trigger responsive
attention to curricular issues. In addition, having appropriate schema and tools will permit us to
evaluate and characterize emerging new computing disciplines and better leverage existing
relationships and infrastructure in their development. The Computing Ontology Project is well
underway. You may hear of its progress in publications and conference presentations in the future.
In the meantime, you may access the set of current volumes in the Computing Curricula Series at
http://www.acm.org/education/curricula.html and http://computer.org/curriculum. At these sites, you
will also find news about various existing and upcoming projects, links to feedback opportunities that are
available, and news about curriculum-related presentations.

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References
[ANSI/IEEE Standard 729-1983] IEEE Standard Glossary of Software Engineering Terminology, The
Institute of Electrical and Electronics Engineers, Inc., NY, 1983.
[AssocDeg] ACM Two-Year College Computing Curricula Task Force. Computing Curricula Guidelines
for Associate-Degree Programs. New York, NY: ACM Press, 1993.
(http://www.acm.org/education/curricula.html)
[CC91] ACM/IEEE-CS Joint Curriculum Task Force. Computing Curricula 1991. Association for
Computing Machinery and the Computer Society of the Institute of Electrical and Electronics Engineers,
1991. (http://www.acm.org/education/curricula.html or http://www.computer.org/curriculum)
[CC2001] ACM/IEEE-Curriculum 2001 Task Force. Computing Curricula 2001, Computer Science.
IEEE Computer Society Press and ACM Press, December 2001. (http://www.computer.org/curriculum or
http://www.acm.org/education/curricula.html)
[CE2004] IEEE/ACM Joint Task Force on Computing Curricula. Computer Engineering 2004.
Curriculum Guidelines for Undergraduate Degree Programs in Computer Engineering. IEEE Computer
Society Press and ACM Press, December 2004. (http://www.computer.org/curriculum or
[HS] Pre-College Task Force Committee of the Education Board of the ACM. ACM Model High School
Computer Science Curriculum. Communications of the ACM, 36(5): 87-90, May1993.
(http://www.acm.org/education/curricula.html)
[IEEE Std 610.12-1990] Standard Glossary of Software Engineering Terminology. The Institute of
Electrical and Electronics Engineers, Inc., NY, 1990.
[IS97] IS ‘97 Model Curriculum and Guidelines for Undergraduate Degree Programs in Information
Systems. Association for Computing Machinery and Association for Information Technology
Professionals, 1997. (http://www.acm.org/education/curricula.html)
[IS2002] ACM/AIS/AITP Joint Task Force on Information Systems Curricula. IS2002 Model Curriculum
and Guidelines for Undergraduate Degree Programs in Information Systems, Association for Computing
Machinery, Association for Information Systems, and Association for Information Technology
Professionals, 2002. (http://www.acm.org/education/curricula.html or
http://www.computer.org/curriculum)
[IT2006] The ACM SIGITE Task Force on IT Curriculum. Information Technology 2006, Curriculum
Guidelines for Undergraduate Degree Programs in Information Technology. As this is written, the IT
curriculum report is in development. We expect the review and development process to be completed in
2006. At the moment, the current draft is called IT2005 and is available for public review and comment.
The most current link to the IT volume can be found at: http://www.acm.org/education/curricula.html.
[K-12] ACM K-12 Task Force Curriculum Committee. A Model Curriculum for K-12 Computer
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[SE2004] IEEE/ACM Joint Task Force on Computing Curricula. Software Engineering 2004, Curriculum
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(http://www.qaa.ac.uk/academicinfrastructure/benchmark/honours/computing.asp)

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Glossary
Algorithms and Complexity – Computational solutions (algorithms) to problems; time and space
complexity with respect to the relationship between the run time and input and the relationship between
memory usage and input as the size of the input grows.

Analysis of Business Requirements – The process through which an information systems or software
application development project determines the optimal capabilities of the target system or application
based on the business goals of the individual user(s) or the user organization(s).

Analysis of Technical Requirements – The process through which a computing development project
determines the computing and communications hardware and software based on the goals of the
individual user(s) or the user organization(s).

Business Models – Various structures, processes, and other mechanisms that businesses and other
organizations use for organizing the way they interact with their primary external stakeholders (e.g.,
customers and suppliers) to achieve their primary goal (e.g., maximization of profit).

Circuits and Systems – The computing and communications hardware and software components that
constitute a computing project or solution.

Computer Architecture and Organization – Form, function, and internal organization of the integrated
components of digital computers (including processors, registers, memory, and input/output devices) and
their associated assembly language instructions sets.

Computer Systems Engineering – A computing discipline that is more prominent in Europe than in
North America. It integrates aspects of CE, CS, and SE, and focuses on the development of complex
systems that require close integration of computer hardware and software. Areas of special emphasis
include design and implementation of embedded and real-time systems, the use of formal methods for
specification of computer systems, and the implementation of systems on specialized-purpose circuits.

Decision Theory – A field of study that develops knowledge and analytical models that together will help
decision makers select among various alternatives that are known (or thought) to lead to specific
consequences.

Digital logic – Sequential and non-sequential logic as applied to computer hardware including circuits
and basic computer organization.

Digital Media Development – The field of computing that deals with the portable storage of digital
information.

Digital Signal Processing – The field of computing that deals with digital filters, time and frequency
transforms, and other digital methods of handling analog signals.

Distributed Systems – Theory and application of multiple, independent, and cooperating computer
systems.

E-business – The use of information and communication technology solutions to implement business
models and internal and external business processes. In a more narrow sense, the term is often used to
refer to the use of Internet technologies to conduct business between firms (B2B), between firms and
consumers (B2C), or among consumers (C2C).

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Electronics – The hardware that constitutes the computing and communications circuits which either
directly operate on electronic signals or run the software which operates on electronic signals. The fields
of computing and communications presently rely completely on electronics.

Embedded Systems - Hardware and software which forms a component of some larger system and
which may be expected to function with minimal human intervention (e.g., an automobile’s cruise control
system).

Engineering Economics for SW – Cost models for the software engineering lifecycle including
development, maintenance, and retirement of software systems.

Engineering Foundations for SW – Engineering design, process, and measurement as applied to
software systems.

Evaluation of Business Performance – The activities that an organization uses to determine how
successful it has been in achieving its goals.
Functional Business Areas – Accounting, finance, marketing, human resource management,
manufacturing, and logistics are examples of functional business areas. Each of these is responsible for a
set of connected business activities which as a whole help a business achieve a specific functional goal
(such as providing a reliable and appropriate set of internal and external business performance measures
in accounting).
General Systems Theory – A field of study that explores the general characteristics of systems in various
areas of human behavior and natural sciences with a special focus on complexity and system component
interdependency. General systems theory had its origins in physics, biology, and engineering, but it has
been utilized in many other fields such as economics, organizational theory, philosophy, sociology, and
information systems.

Graphics and Visualization – Theory and application of computer generated graphics and graphical
representation of data and information including static, dynamic, and animated techniques.

Hardware Testing and Fault Tolerance – The field of study that deals with faster, cheaper, and more
efficient ways of testing hardware (see also Electronics and Circuits and Systems) as well as ways of
making hardware more fault tolerant (able to continue functioning as specified in spite of hardware or
software faults).

Human-Computer Interaction – An organizational practice and academic field of study that focuses on
the processes, methods, and tools that are used for designing and implementing the interaction between
information technology solutions and their users.

Information Management (DB) Theory – Theoretical models for information representation, storage,
and processing.

Information Management (DB) Practice – The activities associated with the analysis, design,
implementation, and management of organizational information resources such as operational databases,
data warehouses, and knowledge management systems.
Information Systems Development – The human activities -- including requirements analysis, logical
and physical design, and system implementation -- that together lead to the creation of new information
systems solutions.

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Integrative Programming –Uses the fundamentals of programming to focus on bringing together
disparate hardware and software systems, building a system with them that smoothly accomplishes more
than the separate systems can accomplish.

Intelligent Systems (AI) – Computer applications that are based on artificial intelligence theory and
techniques including rule-based systems, genetic and evolutionary computation, and self-organizing
systems.

Interpersonal Communication – An area of study that helps computing students improve their oral and
written communication skills for teamwork, presentations, interaction with clients and other informants,
documentation, sales and marketing activities, etc.
Legal / Professional / Ethics / Society – The areas of practice and study within the computing disciplines
that help computing professionals make ethically informed decisions that are within the boundaries of
relevant legal systems and professional codes of conduct.
Management of Information Systems Organization – The processes and structures that are used to
organize and manage the employees and contractors within the organization whose primary
organizational role is to create, maintain, administer, or manage organizational information systems
solutions.

Mathematical Foundations – Those aspects of mathematics that underlie work in the computing
disciplines. The subsets of mathematics that are most relevant to computing vary from one computing
discipline to another. Depending on the discipline, mathematical foundations may include algebra (linear
and abstract), calculus, combinatorics, probability, and/or statistics. The term "mathematical foundations"
sometimes also includes the fields of study and research that are interdisciplinary between mathematics
and computer science such as discrete mathematics, graph theory, and computational complexity theory.

Net Centric: Principles and Design – Includes a range of topics including computer communication
network concepts and protocols, multimedia systems, Web standards and technologies, network security,
wireless and mobile computing, and distributed systems.

Net Centric: Use and Configuration – The organizational activities associated with the selection,
procurement, implementation, configuration, and management of networking technologies.

Operating Systems Principles & Design – Underlying principles and design for the system software that
manages all hardware resources (including the processor, memory, external storage, and input/output
devices) and provides the interface between application software and the bare machine.

Operating Systems Configuration & Use – Installation, configuration, and management of the
operating system on one or more computers.

Organizational Behavior – A field of study within the business discipline of management that focuses
on individual and group-level human behavior in organizations. The core topics include, for example,
individual and group decision making, problem solving, training, incentive structures, and goal setting.
Organizational Change Management – A field of study often associated with the business discipline of
management that focuses on topics that help employees in organizations to manage and cope with
organizational change whether it is a result of internal organizational actions or forces in the external
environment.

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Organizational Theory – A field of study within the business discipline of management that focuses on
the structure of the organizations. This field helps managers decide what types of organizational
structures to use and understand why certain types of structures tend to work better than others. Key
questions focus on centralization/decentralization of power, the selection and use of coordination and
control mechanisms, and breadth and dept of the organizational reporting structures.

Platform Technologies – The field of study which deals with the computing hardware and operating
systems which underlie all application programs.

Programming Fundamentals - Fundamental concepts of procedural programming (including data types,
control structures, functions, arrays, files, and the mechanics of running, testing, and debugging) and
object-oriented programming (including objects, classes, inheritance, and polymorphism).

Project Management – An organizational practice and academic field of study that focuses on the
management approaches, organizational structures and processes, and tools and technologies that together
lead to the best possible outcomes in work that has been organized as a project.
Risk Management (Project, safety risk) – An organizational practice and academic field of study that
focuses on the processes, management approaches, and technologies for identifying risks, determining
their severity level, and choosing and implementing the proper course of action for each risk.

Scientific Computing (Numerical Methods) – Algorithms and the associated methods for computing
discrete approximations used to solving problems involving continuous mathematics.

Security: Issues and Principles – Theory and application of access control to computer systems and the
information contained therein.

Security: Implementation and Management – The organizational activities associated with the
selection, procurement, implementation, configuration, and management of security processes and
technologies for IT infrastructure and applications.

Software Design - An activity that translates the requirements model into a more detailed model that
represents a software solution which typically includes architectural design specifications and detailed
design specifications. [Alternatively, in software engineering, the process of defining the software
architecture (structure), components, modules, interfaces, test approach, and data for a software system to
satisfy specified requirements. [ANSI/IEEE Standard 729-1983] ]

Software Evolution (Maintenance) - (1) The process of modifying a software system or component after
delivery to correct faults, improve performance or other attributes, or adapt to a changed environment.
(2) The process of retaining a hardware system or component in, or restoring it to, a state in which it can
perform its required functions. [IEEE Std 610.12-1990]

Software Modeling and Analysis – An activity that attempts to model customer requirements and
constraints with the objective of understanding what the customer actually needs and thus defining the
actual problem to be solved with software.

Software Process - (1) A sequence of steps performed for a given purpose, for example, the software
development process. (2) An executable unit managed by an operating system scheduler. (3) To perform
operations on data. [IEEE Std 610.12-1990]
Software Quality (Analysis) - (1) A planned and systematic pattern of all actions necessary to provide
adequate confidence that an item or product conforms to established technical requirements. (2) A set of

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activities designed to evaluate the process by which products are developed or manufactured. [IEEE Std
610.12-1990]

Software Verification and Validation - The process of determining whether the requirements for a
system or component are complete and correct, the products of each development phase fulfill the
requirements or conditions imposed by the previous phase, and the final system or component complies
with specified requirements. [IEEE Std 610.12-1990]

Systems Administration – The field of study which deals with the management of computing and
communications resources, including networks, databases, operating systems, applications, and Web
delivery. The management issues include installation, configuration, operation, and maintenance.

Systems Integration – The field of study that deals with the incorporation of computing and
communications resources to create systems that meet specific needs. Elements include organizational
issues, requirements, system architecture, acquisition issues, testing, and quality assurance.

Technical Support – The field of study which deals with solving the problems of the end user of a
computing and/or communications product or system after the product or system has been delivered and
installed.

Theory of Programming Languages – Principles and design of programming languages including
grammars (syntax), semantics, type systems, and various language models (e.g., declarative, functional,
procedural, and object-oriented).

VLSI Design – The field of study that deals with creating electronic solutions to computing and
communications problems or needs. This includes custom integrated circuit (IC) design (which includes
microprocessors and microcontrollers), application-specific IC design (including standard cells and gate
arrays), and programmable hardware (including FPGAs, PGAs, PALs, GALs, etc.).

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Acm 2005

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Acm 2005