Chapter1 conventional softwaremanagement (1)

Chapter 1
Conventional Software
Management

Introduction
Three analyses of the state of the software
engineering industry as of mid 1990s yielded:
Software Development is still highly unpredictable
• Only about 10% of software projects are delivered
successfully on time, within initial budget, and meets user
requirements
The management discipline is more of a discriminator in
success or failure than are technology advances
• The level of software scrap and rework is indicative of an
immature process.
Behold the magnitude of the software problem and
current norms!
But is the ‘theory’ bad? “Practice bad?” Both?
Let’s consider….

I. The Waterfall Model
Recognize that there are numerous variations of
the ‘waterfall model.’
Tailored to many diverse environments
The ‘theory’ behind the waterfall model – good
Oftentimes ignored in the ‘practice’
The ‘practice’ – some good; some poor

Waterfall – Theory
Historical Perspective and Update
Circa 1970: lessons learned and observations
Point 1: There are two essential steps common to the development of
computer programs: analysis and coding - More later on this one.
Point 2: In order to manage and control all of the intellectual freedom
associated with software development, one must introduce several other
‘overhead’ steps, including system requirements definition, software
requirements definition, program design, and testing. These steps
supplement the analysis and coding steps.” (See Fig 1-1, text, p. 7,
which model basic programming steps and large-scale approach)
Point 3: The basic framework … is risky and invites failure. The
testing phases that occurs at the end of the development cycle is the first
event for which timing, storage, input/output transfers, etc. are
experienced as distinguished from analyzed. The resulting design
changes are likely to be so disruptive that the software requirements
upon which the design is based are likely violated. Either the
requirements must be modified or a substantial design change is
warranted.  Discuss.

Suggested Changes ‘Then’ and ‘Now’
1. “Program design” comes first.
Occurs between SRS generation and analysis.
 Program designer looks at storage, timing, data.
Very high level…First glimpse. First concepts…
During analysis: program designer must then impose
storage, timing, and operational constraints to
determine consequences.
Begin design process with program designers, not
analysts and programmers
Design, define, and allocate data processing modes
even if wrong. (allocate functions, database design,
interfacing, processing modes, i/o processing, operating
procedures…. Even if wrong!!)
 Build an overview document – to gain a basic
understanding of system for all stakeholders.

Point 1: Update: We use the term ‘architecture
first’ development rather than program design.
Elaborate: distribution, layered architectures, components
Nowadays, the basic architecture MUST come first.
Recall the RUP: use-case driven, architecture-
centric, iterative development process……
Architecture comes first; then it is designed and
developed in parallel with planning and
requirements definition.
Recall RUP Workflow diagrams….

Point 2: Document the Design
Development efforts required huge amounts of
documentation – manuals for everything
• User manuals; operation manuals, program maintenance
manuals, staff user manuals, test manuals…
• Most of us would like to ‘ignore’ documentation. 
Each designer MUST communicate with various
stakeholders: interface designers, managers,
customers, testers, developers, …..

Point 2: Update: Document the Design
Now, we concentrate primarily on ‘artifacts’ –
those models produced as a result of developing an
architecture, performing analysis, capturing
requirements, and deriving a design solution
• Include Use Cases, static models (class diagrams, state
diagrams, activity diagrams), dynamic models (sequence
and collaboration diagrams), domain models, glossaries,
supplementary specifications (constraints, operational
environmental constraints, distribution, ….)
• Modern tools / notations, and methods produce self-
documenting artifacts from development activities.
• Visual modeling provides considerable documentation

Point 3: Do it twice.
History argues that the delivered version is really version #2.
Microcosm of software development.
Version 1, major problems and alternatives are addressed –
the ‘big cookies’ such as communications, interfacing, data
modeling, platforms, operational constraints, other
constraints. Plan to throw first version away sometimes…
Version 2, is a refinement of version 1 where the major
requirements are implemented.
Version 1 often austere; Version 2 addressed shortcomings!
Point 3: Update.
This approach is a precursor to architecture-first
development (see RUP). Initial engineering is done. Forms
the basis for iterative development and addressing risk!

Point 4: Then: Plan, Control, and Monitor
Testing.
Largest consumer of project resources (manpower,
computing time, …) is the test phase.
 Phase of greatest risk – in terms of cost and schedule. (EST
1…)
• Occurs last, when alternatives are least available, and expenses are at
a maximum.
• Typically that phase that is shortchanged the most
To do:
• 1. Employ a non-vested team of test specialists – not responsible for
original design.
• 2. Employ visual inspections to spot obvious errors (code reviews,
other technical reviews and interfaces)
• 3. Test every logic path
• 4. Employ final checkout on target computer…..

Point 4: Now: Plan, Control, and Monitor
Testing.
Items 1 and 4 are still valid.
• 1) Use a test team not involved in the development of the system –
at least for testing other than ‘unit testing…’
• 4) Employ final checkout on target computer….
Item 2 (software inspections) – good years ago, but modern
development environments obviate this need. Many code
analyzers, optimizing compilers, static and dynamic
analyzers are available to automatically assist…
• May still yield good results – but not for significant problems!
Stylistic!
Item 3 (testing every path) is impossible. Very difficult
with distributed systems, reusable components (necessary?),
and other factors…. (aspects)

Point 5 – Old: Involve the Customer
Old advice: involve customer in requirements
definition, preliminary software review,
preliminary program design (critical design
review briefings…)
Now: Involving the customer and all stakeholders
is critical to overall project success.
Demonstrate increments; solicit feedback;
embrace change; cyclic and iterative and
evolving software. Address risk early…..

Overall Appraisal of Waterfall Model
Criticism of the waterfall model is
misplaced.
Theory is fine.
Practice is what was poor!

But: Less than 20% success rate
The Software Development Plan:
Old Version
Define precise requirements
Define precise plan to deliver system
Constrained by specified time and budget
Execute and track to plan
Stakeholder
Satisfaction Space
Initial Project SituationInitial Project Situation
 Reused or legacy assetsReused or legacy assets
 Detailed plans, scopeDetailed plans, scope
Planned Path

1.1.2 In Practice
Characteristics of Conventional Process – as it has
been applied (in general)
Projects not delivered on-time, not within initial
budget, and rarely met user requirements
Projects frequently had:
1. Protracted integration and late design breakage
2. Late risk resolution
3. Requirements-driven functional decomposition
4. Adversarial stakeholder relationships
5. Focus on documents and review meetings
Let’s look at these five major problems…

Sequential Activities:
Requirements Design Code Integration
Symptoms of conventional
waterfall process
 Late design breakage
 40% effort on integration & test
Late Design
Breakage
100%
Project Schedule
DevelopmentProgress
(%coded)
Original
Target Date
Integration
Begins
Completion
Date
. Early paper designs and thorough briefings
. Commitment to code very late in cycle
. Integration nightmares due to unforeseen
implementation and interface issues
. Heavy budget and schedule pressure
. Late ‘shoe-horning’ of non-optimal fixes
with no time for redesign!!!!
. A very fragile, un-maintainable product and
almost always: delivered late.
1. Protracted Integration and Late Design Breakage

Expenditures per activity for a
Conventional Software Project
Activity Cost
Management 5%
Requirements 5%
Design 10%
Code and unit test 30%
Integration and Test 40%
Deployment 5%
Environment 5%
Total 100%
 Lots of time spent on ‘perfecting the software design’ prior to
commitment to code.
 Typically had: requirements in English, design in flowcharts, detailed
design in pdl, and implementations in Fortran, Cobol, or C
Waterfall model  late integration and performance showstoppers.
Could only perform testing ‘at the end’ (other than unit testing)
Testing ‘should have’ required 40% of life-cycle resources: often didn’t!!

2. Late Risk Resolution
Problem here:  focused on early paper artifacts.
Real issues – still unknown and hard to grasp.
Difficult to resolve risk during requirements when many
key items still not fully understood.
Even in design, when requirements better understood, still
difficult to get objective assessment.
• Risks were at a very high level
During coding, some risks resolved, BUT during
 Integration, many risks were quite clear and changes to
many artifacts and retrenchment often had to occur
While much ‘retrenchment ‘did’ occur, it often caused missed
dates, delayed requirement compliance, or, at a
minimum, sacrificed quality (extensibility,
maintainability, loss of original design integrity, and
more).
Quick fixes, often without documentation occurred a lot!

3. Requirements-Driven Functional Decomposition
Traditionally, software development processes have been requirements-driven.
Developers: assumed requirement specs: complete, clear, necessary, feasible, and
remaining constant! This is RARELY the case!!!!
All too often, too much time spent on equally treating ‘all’ requirements rather
than on critical ones.
Much time spent on documentation on topics (traceability, testability, etc.) that
was later made obsolete as ‘DRIVING REQUIREMENTS AND SUBSEQUENT
DESIGN UNDERSTANDING EVOLVE.’ We do not KNOW all we’d like to
know ‘up front.’
Too much time addressing all of the scripted requirements
• normally listed in tables, decision-logic tables, flowcharts, and plain, old text.
• Much brainpower wasted on the ‘lesser’ requirements.
Also, assumption that all requirements could be captured as ‘functions’ and
resulting decomposition of these functions.
Functions, sub-functions, etc. became the basis for contracts and work
apportionment, while ignoring major architectural-driven approaches and
requirements that are ‘threaded’ throughout functions and that transcend
individual functions…... (security; authentication; persistency; performance…)
Fallacy: all requirements can be completely specified ‘up front’ and (and
decomposed) via functions.

4. Adversarial Stakeholder Relationships (1 of 2)
Who are stakeholders? Discuss….Quite a diverse group!
Adversarial relationships OFTEN true!
Misunderstanding of documentation usually written in
English and with business jargon.
Paper transmission of requirements – only method used….
No real modeling, universally-agreed-to languages with
common notations; (no GUIs, network components already
available; Most systems were ‘custom.’)
Subjective reviews / opinions. Generally without value!
…more
Management Reviews; Technical Reviews!

4. Adversarial Stakeholder Relationships
Common Occurrences:
Common events with contractual software:
1. Contractor prepared a draft contract-deliverable document that
constituted an intermediate artifact and delivered it to the customer for
approval. (usually done after interviews, questionnaires, meetings…)
2. Customer was expected to provide comments
(typically within 15-30 days.)
3. Contractor incorporated these comments and submitted
(typically 15-30 days) a final version for approval.
Evaluation:
Overhead of paper was huge and ‘intolerable.’ Volumes of paper! (often
under-read)
Strained contractor/customer relationships
Mutual distrust – basis for much litigation
Often, once approved, rendered obsolete later….(living document?)

5. Focus on Documents and Review Meetings
A very documentation-intensive approach.
Insufficient attention on producing credible ‘increments’ of the
desired products.
Big bang approach – all FDs delivered at once;
All Design Specs ‘ok’d’ at once and ‘briefed’…
Milestones ‘commemorated’ via review meetings – technical,
managerial, ….. Everyone nodding and smiling often…
Incredible energies expended on producing paper documentation to
show progress versus efforts to address real risk issues and
integration issues.
Stakeholders often did not go through design…
Very VERY low value in meetings and high costs
• Travel, accommodations…..
Many issues could have been averted early during development –
during early life-cycle phases rather than encountered huge problems
late….but…

Continuing….
Typical Software product design Reviews….
1. Big briefing to a diverse audience
Results: only a small percentage of the audience understands the
software
Briefings and documents expose few of the important assets and risks
of complex software.
2. A design that appears to be compliant
There is no tangible evidence of compliance
Compliance with ambiguous requirements is of little value.
3. Coverage of requirements (typically hundreds….)
Few (tens) are in reality the real design drivers, but many presented
Dealing with all requirements dilutes the focus on critical drivers.
4. A design considered ‘innocent until proven guilty’
The design is always guilty
Design flaws are exposed later in the life cycle.

1.2 Conventional Software
Management Performance
Very few changes from Barry Boehm’s
“industrial software metrics” from 1987.
Most still generally describe some of the
fundamental economic relationships that are
derived from years of practice:
What follows is Barry’s top ten (and your
author’s (and my) comments.

Basic Software Economics…
1. Finding and fixing a software problem after delivery costs 100
times more than fining and fixing the problem in early design phases.
Flat true.
2. You can compress software development schedules 25% of
nominal, but no more.
Addition of people requires more management overhead and training
of people.
Still a good heuristic. Some compression is sometimes possible! Be
careful! Oftentimes it is a killer to add people….(Discuss later)
3. For every dollar you spend on development, you will spend two
dollars on maintenance. We HOPE this is true!
Hope so. Long life cycles mean revenue…Still, hard to tell
Product’s success in market place is driver.
Successful products will have much higher ratios of “maintenance to
development”…..
One of a kind development will most likely NOT spend this kind of
money on maintenance .
• Examples: implementation / conversion subsystems…..
• Conversion software….

Basic Software Economics (cont)
4. Software development and maintenance costs are primarily a
function of the number of source lines of code.
Generally true. Component-based development may dilute
this as might reuse - but not in common use in the past.
5. Variations among people account for the biggest differences
in software productivity.
Always try to hire good people. But we cannot always to that. Balance
is critical. Don’t want all team members trying to self-actualize and
become heroes. Build the ‘team concept.’ While there is no “I” in
‘team”, there is an implicit “we.”
6. Overall ratio of software to hardware costs is still growing.
In 1955 it was 15:85; In 1985, it was 85:15. Now? I don’t
know.
While true, impacting these figures is the ever-increasing demand for
functionality and attendant complexity. They appear w/o bound.

7.  Only about 15% of software development effort is
devoted to programming. (Sorry! But this is the way it is!)
Approximately true. This figure has been used for years –
and is shattering to a lot of programmers – especially ‘new’
ones. And, this 15% is only for the development! It does not
include, hopefully, some 65% - 70% of the overall total life
cycle expenses based on maintenance!!
8. Software systems and products typically cost three times as
much per SLOC as individual software programs. Software-
system products, that is system of systems, cost nine times as
much.
A real fact: the more software you build, the more
expensive it is per source line. Why do you think?
Discuss!

9. Walkthroughs catch 60% of the errors.
Usually good for catching stylistic things; sometimes errors, but
usually do not represent / require the deep analysis necessary to
catch significant shortcomings.
Major problems, such as performance, resource contention, …
are not caught.
10. 80% of the contribution comes from 20% of the contributors.
80/20 rule applies to many things: see text. But pretty correct!
• See text for a number of these – which are ‘generally’ true….

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