BUSINESS RULE MANAGEMENT FRAMEWORK FOR ENTERPRISE WEB SERVICES

International Journal on Web Service Computing (IJWSC), Vol.1, No.2, December 2010
DOI : 10.5121/ijwsc.2010.1202 15
BUSINESS RULE MANAGEMENT
FRAMEWORK FOR ENTERPRISE WEB
SERVICES
Thirumaran. M1
and Ilavarasan. E2
and Thanigaivel. K3
and Abarna. S4
1
Department of Computer science and Engineering, Pondicherry Engg College, India.
thirumaran@pec.edu
2
eilavarasan@pec.edu
3
thanigaivel20@pec.edu
4
abarna.pec@gmail.com
1. ABSTRACT
Making a business rule extraction more dynamic is an open issue, and we think it is feasible if
we decompose the business process structure in a set of rules, each of them representing a transition of
the business process. As a consequence the business process engine can be realized by reusing and
integrating an existing Rule Engine. We are proposing a way for extracting the business rules and then
to modify it at the runtime. Business rules specifies the constraints that affect the behaviors and also
specifies the derivation of conditions that affect the execution flow. The rules can be extracted from use
cases, specifications or system code. But since not many enterprises capture their business rules in a
structured, explicit form like documents or implicit software codes, they need to be identified first, before
being captured and managed. These rules change more often than the processes themselves, but
changing and managing business rules is a complex task beyond the abilities of most business analysts.
The capturing process focuses on the identification of the potential business rules sources. As business
logic requirements change, business analysts can update the business logic without enlisting the aid of
the IT staff. The new logic is immediately available to all client applications. In current trend the rules
are modified or changed in the static time phase. But this paper provides to change the rules at the run
time. Here the rules are extracted from the services and can be a changed dynamically. The existing
rules are modified and attached to source code without hindering service to the end user which can be
achieved with source control systems. When the rules are revised, it provides a path in budding new
business logic. This new business logic can be adopted for the efficient software development.
2. KEYWORDS
Dynamic Rule Execution, Business process, Business rules, Business Rules Approaches.
3. INTRODUCTION
A Business Rule Management System is a software system used to define, deploy, execute,
monitor and maintain the variety and complexity of decision logic that is used by operational
systems within an organization or enterprise. This logic, also referred to as business rules,
includes policies, requirements, and conditional statements that are used to determine the
tactical actions that take place in applications and systems. A business rule management system

16
(BRMS) enables organizational policies – and the operational decisions associated with those
policies – to be defined, deployed, monitored and maintained separately from core application
code. By externalizing business rules and providing tools to manage them, a BRMS allows
business experts to define and maintain the decisions that guide systems behavior, reducing the
amount of time and effort required to update production systems, and increasing the
organization’s ability to respond to changes in the business environment. BRMS solutions
automate policies in custom and composite business applications. They lower application
maintenance costs, facilitate more accurate and consistent business policy implementation
across applications, and improve collaboration between your business and IT departments.
A business process defines the context and the logical relationships between activities, and
also specifies both the order of invocations (control flow) and the rules for data transfer (data
flow). Such activities are configured in order to produce a specific output and associated with
specific objectives. A business rule is a statement that defines or constrains some aspect of the
business. Business rules are usually expressed either as constraints or in the form “if condition
then action”. They provide the means to express, manage and update different kind of
components contained into the whole business domain. In this way, such rules have to be
expressed in terms of the defined activities and further integrated with the process specification.
The definition of a process and business rules requires often specific skills, usually related to
people with a high level of expertise in design and programming. Another common problem is
the lack of flexibility related to: business rules derivation based on dynamic changes of the
business context. On the other hand, we have seen that many approaches are not completely
dynamic and effective when we need to automatically modify the business process instance, by
adding or deleting an activity, according to changes of business process context. To address
these issues, we propose an approach focused on providing a more dynamic and flexible
adaptation of the business rules. The main purpose of our approach is to increase the
adaptability of the system, by identify and change or alter the rules in the run time of any
application. This can be implemented with the help of JESS language. The JESS language
supports dynamic changes that can be made in any real time application.
4. LITERATURE SURVEY
Business Process Management (BPM) is an established discipline for building,
maintaining, and evolving large enterprise systems on the basis of business process models. A
business process model is a flow-oriented representation of a set of work practices aimed at
achieving a goal, such as processing a customer request or complaint, satisfying a regulatory
requirement, etc. The Business Process Modeling Notation (BPMN) is gaining adoption as a
standard notation for capturing business processes. The main purpose of business process
models generally, and BPMN models in particular, is to facilitate communication between
domain analysts and to support decision-making based on techniques such as cost analysis,
scenario analysis, and simulation Chun Ouyang [1] proposed an acyclic BPMN model, or an
acyclic fragment of a BPMN model, falls under the class if it satisfies a number of semantic
conditions such as absence of deadlock. He applied Petri net analysis techniques to statically
check these semantic conditions on the source BPMN model. According to Michael zur
Muehlen [2], Business Processes are sets of activities that create value for a customer. While
research in Business Process Management initially focused on the documentation and
organizational governance of processes, organizations are increasingly automating processes
using workflow systems, and are building elaborate management systems around their
processes. Such management infrastructures integrate modeling, automation, and business
intelligence applications. The inclusion of compliance management activities is a logical next

17
step in governing the business process life cycle. Josef Schiefer [3] says that Business Process
Management (BPM) systems are software solutions that support the management of the life
cycle of a business process. For the execution of business processes, many organizations are
increasingly using process engines supporting standard-based process models (such as
WSBPEL) to improve the efficiency of their processes and keep the testing independent from
specific middleware. A major challenge of current BPM solutions is to continuously monitor
ongoing activities in a business environment and to respond to business events with minimal
latency. One of the most promising concepts that approaches the problems of closed-loop
decision making and the lack of gaining real-time business knowledge is the concept of
Complex Event Processing (CEP), The system automatically discovers and analyzes business
situations or exceptions and can create reactive and proactive responses, such as generating
early warnings, preventing damage, loss or excessive cost, exploiting time-critical business
opportunities, or adapting business systems with minimal latency. Claire Costello [4] says A
business process as a complete set of end-to-end activities that together create value for the
customer. Business process management is the ability to orchestrate and control the execution
of a business process across heterogeneous systems and allow users to view the components of
an infrastructure from a process view rather than set of applications and databases. Anca
Andreescu [5] says every organization operates according to a set o business rules. These may
be external rules, coming from legal regulations that must be observed by all organizations
acting in a certain field, or internal rules which define the organization’s business politics and
aim to ensure competitive advantages in the market. Starting from the previous observations, it
is obvious the important role that business rules play within the development process of a
software system. Milan Milanović1 [6] proposed that BPM languages have limited support for
representing logical expressions, business vocabularies, and business rules, which severely
limits their flexibility and expressivity. To address these challenges, he integrated business rule
modeling constructs of the REWERSE Rule Markup Language (R2ML) with the Business
Process Modeling Notation (BPMN), resulting in a rBPMN proposal. Olegas Vasilecas [7] says
Business rules make an important and integral part of each information system (IS) by
expressing business logic, constraints of concepts, and their interpretation and relationships.
Therefore it is relevant to pay special attention to business rules in development of information
systems. Rules related to domain structure and behavior are presented in data, states, processes
and other IS models. Taking into account that rules are expressed in several models, there is a
risk that overall specification is inconsistent. Unambiguous models are crucial for the
successful implementation of IS models transformation and finally code generation tasks.
Therefore it is necessary to check consistency among related rules models. The problem of
models inconsistency can be solved by using of formal or partially formal models with
constraints. However formal models are often too complex to be used in practice. Semi-formal
models are widely used, but constraints used in such a models often are suitable only for one
model and relationships among models are not defined. He suggests extending of IS approach
based on semi-formal models and constraints, by adding the consistency rules for IS models.
Anis Charfi [8] applied the divide and conquer principle to web service composition by
explicitly separating business rules from the process specification. The combination of the
business rules approach with the process-oriented composition solves a twofold problem. First,
he provided a solution to the problem of dynamic adaptation of the composition. In fact, current
standards for process-based web service composition are not capable to deal with the flexibility
requirements of composite web services. Second, business rules are important assets of a
business organization that embody valuable domain knowledge. So, it is no longer acceptable
to bury them in the rest of the composition. Bruno de Moura Araujo [9] proposed Business
rules (BR) are declarations which constrain, derive and give conditions for existence,

18
representing the knowledge of the business. BRs are not descriptions of a process or processing.
Rather, they define the conditions under which a process is carried out or the new conditions
that will exist after a process has been completed. BR can be represented using Semantics of
Business Vocabulary and Rules (SBVR). SBVR is appropriate to be used by business experts,
since it allows the representation of business vocabulary and rules using controlled natural
language. Business vocabulary concepts can be automatically transformed into conceptual
models, like the UML class model. Nicholas Zsifkov [10] says Enterprise business rules are
usually defined as constraints or as metadata about business operations: on the business side,
business rules are special policies that define constraints/metadata about the business operation;
on the information system (implementation) side, business rules are constraints about the data,
about data manipulation and about system processes. Antonio Oliveira Filho [11] proposed a
new traceability technique that defines dependency links with the same semantics that can be
observed in the relationships among business rules. The goal of the technique is to provide rates
of recall and precision of 100% for changes in software requirements that correspond to
business rules. Jose F. Mejia Bernal [12] says decomposing the initial business process
structure in a set of rules is a procedure based on pattern identification. This approach consists
of two phases: mapping of business process to rules, and reliable adaptation of the business
process according to the context data. The first phase is executed to provide a representation of
the initial business process definition in terms of rules. The second phase is applied to provide a
reliable workflow process modification.
Timon C. Du and Hsing-Ling Chen propose an active collaboration and negotiation
framework (ACNF), which is a negotiation support system that uses active documents with
embedded business logics or business rules that can adapt to different collaborative strategies in
a business-to-business (B2B) environment [13]. Sam Weber and Isabelle Rouvellou describe a
fully functional prototype middleware system which provides the users to control software
components without the need of programming knowledge. Thus the core applications need not
be altered for anticipated changes from external factors. In this system, application behavior
modification is fast and easy, making this middleware suitable for frequently changing
programs [14]. H. M. Sneed[15], in the context of reverse engineering source code into UML
diagrams many tools and approaches have been developed.CPP2XMI is a reverse engineering
tool which lows extracting UML class, sequence and activity diagrams in XMI format from
C++ source code. Sangseung Kang[16], Business rules are business statements that define some
aspect of a business. They describe, constrain and control the structure, operations and strategy
of the business. In his paper, he analyzes business rules and business rule systems, and present
requirements and considerations for the business rule expression and system. Olga Levina[17],
suggests an extraction process for business rules identification from business process models.
Applying this process introduces a structured approach and management aspects within rules
discovery by focusing on rule sources that are important for the process goal and providing a
rule structure. Mohammed Alawairdhi[18], suggests a business-logic-based framework for
evolving software systems is proposed. The goal of the framework is evolving software in a
higher abstract layer. Olegas Vasilecas[19], suggests The rules are expressed in several
models, there is a risk that overall specification is inconsistent. Unambiguous models are
crucial for the successful implementation of IS models transformation and finally code
generation tasks. Therefore it is necessary to check consistency among related rules models.
The problem of models inconsistency can be solved by using of formal or partially formal
models with constraints. According to Anis Charfi[20], the Business Rules Group , a business
rule is a statement that defines or constrains some aspect of the business. It is intended to assert
business structure or to control the behavior of the business. Business rules are usually

19
expressed either as constraints or in the form if conditions then action. The conditions are also
called rule premises. The business rule approach encompasses a collection of terms
(definitions), facts (connection between terms) and rules (computation, constraints and
conditional logic). Terms and Facts are statements that contain sensible business relevant
observations, whereas rules are statements used to discover new information or guide decision
making. Jose F. Mejia Bernal[21], proposed a way for representing Dynamic Business Process
in terms of Rules based on patterns identification. With this approach it is easy to apply on a
business process instance both user-based personalization rules and automatic rules inferred by
an underlying context-aware system. Gulnoza Ziyaeva proposed framework to enable the
content-based intelligent routing path construction and message routing in ESB which defines
the routing tables and mechanisms of message routings and facilitate the service selection based
on message content [22].
5. EXISTING SYSTEM
In existing system the Business Rules can be changed or modified only during the inert
time period. So the main aim of this Project is to provide Business Rules that can be changed at
the Run Time. Here the existing rules are modified and can be attached to source code without
hindering service to the end user which can be achieved with source control systems. Once the
services have been identified, the rules can be extracted and service can be provided
dynamically. To provide this service we are going to make use of JESS language.
6. BRMS architecture
6.1. Rule capturing
Rule isolation and extraction is performed by tracing logic paths based on various
selection criteria. This includes logic leading to the creation of a given output variable, logic
linked to some type of conditional and logic associated with a given input transaction
type. Analysts must review a rule after extraction in order to use it as is, extract again based on
a different criteria or subset the extracted rule further. These techniques are somewhat tool
dependent, but it is important to establish an initial extraction criteria regardless of the tool
being applied.
Required rule extraction tool criteria minimally includes an ability to "slice" out a rule
based on a specified selection criteria. Since business rules do not limit themselves to the
confines of a source program, extraction tools must be able to analyze logic across program
boundaries. Beyond that, a rule extraction tool should be able to bypass or highlight
implementation dependent logic, store an extracted rule, further extract against a previously
extracted rule, display a rule in varying formats to promote understandability and transform an
extracted rule into a reusable format. Certain tools can load a system into its knowledge base
and transform it into predicate logic. Rule analysis is then facilitated through cross system
extraction and simplification techniques. Rules may be displayed in decision vectors or as
source code. The real power of are that they allow IT professionals and non-technical analysts,
to examine extracted rules and verify what functions a system is actually performing. While
most tools offer static source code analysis to support rule extraction, other tools provide
dynamic analysis by tracing logic paths during program execution.

20
Figure 1
Figure 1. BRMS Architecture
Dynamic analysis is performed when a program is executed, dynamic analysis can
capture a logic path based on the transaction being performed. Sophisticated tools support the
creation of a union of slices allowing analysts to fine tune extracted views.
6.2. Rule Repository
A business rule repository is a system in which company uses to document, update, and keep
track of the business needs and rules regarding your projects. Having a central repository to
store these rules will allow developers and business owners access to rules, and any questions
regarding business projects.
External
Application
Rule Repository
Decision Service
Rule Server
Rule
Engine
Business
Integrated
Development
Environment
Rule
Management
Application
Data
Source
Dynamic
Rule
Version
Access
Dynamic
Rule
Extraction

21
6.3. Decision service
A decision service is some kind of software component that acts as a business logic
black box: other parts of a system present it with data, it makes potentially-complex business
'decisions' and returns some result. Typically, this is a component of a service-oriented
architecture that encapsulates the business logic required to make business decisions, and which
is called by applications that do not contain this logic themselves. In such an architecture, this
communication typically uses web services. The first thing a Decision Service does is isolate
the logic behind these business decisions, separating it from business processes and the
mechanical operations of procedural application code. Treating decision logic as a manageable
enterprise resource in this way means you can reuse it across multiple applications in many
different operational environments. A centralized approach to decision automation can also
eliminate the time, cost and technical risk of trying to reprogram multiple individual systems
simultaneously to keep up with changing business requirements. For instance, the rules for
paying an insurance claim can be removed from the definition of the claims processing business
process. These rules can be managed independently, important as the legislative change cycle is
different from the business cycle that drives process change. They can also be re-used, for
instance to help customers tell if they have a valid claim before submitting it or to support
third-party agents. The same rules can be in multiple decision services.
7. BENEFIT IN USING BRMS
Generally the rule capturing process focuses on the identification of the potential
business rules sources. As business logic requirements change, business analysts can update the
business logic without enlisting the aid of the IT staff. The new logic is immediately available
to all client applications. All these process are done in run time of any real time application.
This approach can be implemented with JESS language. Since JESS has an advantage of
changing the business rules at the run time. First the rule which is to be changed is checked
with the rules which are in rule repository. If the rules are already present in the repository
means the rules are changed or modified for the particular application. Suppose the rules are not
in the rule repository then it provides an option of adding new rules to rule repository. Based on
this technique the following process is carried out. Here there are some examples of business
rules which had been changed to JESS.
Algorithm for converting Business Rule to JESS
Procedure
Convert business rules Jess
def rule(rule)
get the rule
rule  string defining the business policy
Convert the rule into java expression
Split the expression into operators, operands, parenthesis and store it into array
arr[]  split(operator, operand, parenthesis)
Backtrack the array and assign the elements to a string array
for i  n to 1 j  1 to n do
element  arr[i]
str[j]  element
end for

22
pass the array str[] to the function convert
input[]  str[]
function convert(input[])
do
//Read the next element.
e  input.next()
if e is operand then
outstr  e
end if
if e = ) then
stack.push()  e // Push the operator on stack
end if
do
if e is an operator then // stack is empty, push operator on stack.
if stack = empty then
stack.push()  e
end if
if stack.top  ) then
stack.push()  e
end if
if e.priority == 0 then
stack.push()  e
else
temp  stack.pop()
outstr  temp
end if
while (operator)
if e is ( then // a opening parenthesis, pop operators from stack
if stack.pop() == ) then
discard;
else
outstr  stack.pop() // add them to output string
end if
end if
If there is more input go to step 2
while(input.next == null)
do
outstr  stack.pop()
while(stack == empty)
JessExp  reverse(outstr) //Reverse the string
end function
end procedure
8. BUSINESS RULE AND JESS SYNTAX
8.1. Rules For Car Licence

23
Table 1. Rules for Car Licence
S.N
O
Rule Syntax JESS Syntax
1 Car must
not be
rented to
customers
without a
valid
license
number.
if( Customer.ValidLicenceNumber
== FALSE )
{
application.Stat
us = Reject;
Customer.Eligi
bile = false;
}
(def rule no car rented without lenience no)
(if(=(Customer.ValidLicenceNumber ? true)
=(add(application.status)(/?reject)
(add(customer.eligible)(/?false)
2 Car must
not be
rented to
customers
of Age
less than
18.
if( Customer.age 18 )
{
application.Stat
us = Reject;
Customer.Eligi
bile = false;
}
(def rule no car rented to customer of age less
than 18)
(if(=(customer.age ? 18)(age?age)
3 Car must
not be
rented to
customers
with bad
history
level 3
if( Customer.BadHistoryLevel ==
3 )
{
application.Stat
us = Reject;
Customer.Eligi
bile = false;
}
(def rule no car to customer of bad history level
3)
(if(=(Custome.badhistorylevel ? 3)
4 Rent for
small cars
is 80 aud
per day
if (Customer.Eligible == true)
{
if( Car.type == Small )
{
rent.RentPerDay = 80;
}
(def rule rent for small car is 80/day)
(if(=(Customer.Eligible? true)
{
if(=(cartype?small)
{
=add(rent.perday)(/?price 80))
}
5 Rent for
awd cars
is 100 aud
per day.
if( Car.type == AWD )
{
}
(def rule rent for awd cars 100/day)
(if(=(car.type?AWD)
{
=add(rent.perday)(/?price 100)
}

24
6 Rent for
luxury
cars is 150
aud per
day
if( Car.type == Luxury )
{
}
(def rule rent for luxury cars 150/day)
(if(=(car.type?luxury)
{
=add(rent.perday)(/?price 150)
}
7 Rent
payable is
calculated
as the
product of
rentperday
and
rentalperi
od in
days.
{
rent.RentPayable =
rent.RentPerDay * rent.No of rent
days;
if (CustomerBadHistoryLevel
0)
}
(def rule rent calculated as the product of
rentperday and rentalperiod in days )
(rent.rentpayable)(=(*(?rentperday?rentalperio
d)))
(if((Custome.badhistorylevel ? 0)
=(add(rent.rentpayable)(price?price)
8 Penalty of
20 % of
rent must
be applied
for
customers
with bad
history
level 2.
2
{
rent.PenaltyFee =
rent.RentPayable * 0.2;
}
(def rule Penalty of 20 % of rent for customers
with bad history level 2)
(if(=?Customer.BadHistoryLevel?2)
{
=
add(rent.penaltyfee)(=(*(?rent.rentpayable?0.2)
))
9 Penalty of
10 % of
rent must
be applied
for
customers
with bad
history
level 1.
1 )
{
rent.PenaltyFee =
rent.RentPayable * 0.1;
}
}
(def rule Penalty of 10 % of rent for customers
with bad history level 1)
(if(=?Customer.BadHistoryLevel?1)
{
=
add(rent.penaltyfee)(=(*(?rent.rentpayable?0.1)
))
10 Total
amount
payable is
calculated
as the sum
of rent
payable
and
penalty if
any.
{
rent.TotalAmountPayable =
rent.RentPerDay +
rent.PenaltyFee;
}
else
{
}
(def rule Total amount payable as the sum of
rent payable and penalty.)
{
(rent.TotalAmountPayable)(=(+(?
rent.RentPerDay? rent.PenaltyFee)))
}
=(add(rent.TotalAmountPayable)(price?price)

25
8.2. Rules for Banking
Table 2. Rules for Banking
S.NO Rule Syntax JESS syntax
1 1. A person is defined
high if atleast one of the
following is true:
• The person
should be VIP.
• The person
should have
current balance of
$500.
• The person
should have
account for more
than 5 years.
If(bal 500 year
5 )
{
Print(“the person is
VIP”)
}
(def rule person current balance
500 and account more than 5
years)
(if((bal?500))
{
(if((year?5))
=(add(the person is
VIP))(VIP?VIP)
2 A withdrawal from an
account may be made only
• If the is active
and
• Account balance
should be greater
than zero.
If( acc=active)
{
If( bal0)
{
Printf(“ withdrawal is
made”)
(def rule withdrawal is done if
account is active and balance is
greater than zero)
(if(=(acc?active))
{
(if((bal?0)
{
=add(withdrawal is made)(/
money?money)
3 Income Rule if((basic sal other
income)0))
{
income status =valid;
}
(def rule income)
(if((?basic sal?other income?0)
=add(income status)(=?valid)
4 Commitment status rule if (ID=ID)
{
if( creditcardbal500)
{
print (“ compute
commitments”)
}
(def rule commitment)
(if(=(ID?ID))
{
(if((creditcardbal?500))
{
=(add(compute commitments))
}
5 Employment status rule if( Employmenttype
months18)
{
employment status=valid
}
(def rule employment status)
(if((?employmenttype?months?18)))
{
=add(employment status)(=?valid)
}
6 Residency status rule if(place of residence
time in months18)
{
Residency status=valid;
}
(def rule residency status )
(if((?place of residence?time in
months?18)
=add(residency status)(/?valid)

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8.3 Ticket Reservation
Table 3. Rules for Ticket Reservation
S.NO Rule Syntax JESS syntax
1 The User must have
to login .
If(user.acctno==”false”)
{
User.login=invalid;
}
(def rule user login)
(if(=(user.acctno?false)))
=add(user.login)(=?invalid)
2 The available seats
in the train should
be visible to the
user.
• Provide Date,
Time (arrival
time, departure
time).
If( user.acctno=valid)
{
User.date=”journey date”;
User.atime=”arrival time”;
User.dtime=”depature time”;
}
(def rule for providing date, arrival
time, depature time)
(if(=(user.acctno?valid)))
=add(user.date) (=?journey date)
add(user.atime) (=?arrival time)
add(user.dtime) (=?depaturetime)
3 If the required train
is available book the
ticket.
If(user.train==”available”)
{
User.ticket=”true”;
}
(def rule for booking ticket)
(if(=(user.train?available)))
=add(user.ticket)(=?true)
4 The ticket must
contain details such
as
Id number
• Name
• No. of
passengers
• Seat no
• Coach no
• Class
(I,II,III)
If(user.ticket==”true”)
{
User.ticket.id=”id number”;
User.ticket.name=”name”;
User.ticket.passenger=”no.of
passenger”;
User.ticket.seat=”seat no”;
User.ticket.coach=”coach no”;
}
(def rule for ticket details)
(if(=(user.ticket?true))
{
=add(User.ticket.id)(=?id number)
=add(User.ticket.name)(=?name)
=add(User.ticket.passenger)(=?no.of
passenger)
=add(User.ticket.seat)(=?seat no)
=add(User.ticket.coach)(=?coach no)
5 The some amount of
cancellation charge
must be deduced
from the user.
If(ticket.status==”cancelled”)
{
User.account=amount-20;
}
If(ticket.status==”cancelled”){
If(user.account==”deduced”)
{
Return balance;
}
}
(def rule for cancelling ticket)
(if(=(ticket.status?cancelled)))
{
(User.account)(=(-(?amount?20)
}
(if(=(ticket.status?cancelled)))
(if(=(user.account?deduced)))
{
=add(return balance)(price?price)
}

27
9. Experimental Approach
The Extraction of business rules can be created using .net framework. For storing the
Business rules we are making use of MS access database. The Business rules for the several
applications are first identified. If the rules are to be changed, here provide an option of editing
the rule and store it in the repository. Suppose if the rules are already present in the repository it
can be mapped and extracted otherwise new rules can be added to it. Moreover additional
functions are added to this framework. The functions such as modify, update, extend. The
application we developed is shown below.
9.1. Screenshots
10. Conclusion
Changing the business rules dynamically, with the help of Jess language, has the
purpose of providing flexibility, correctness and consistency. This paper provides a reliable and
more flexible approach to handle dynamic changes in business rules. The Rule extraction can
be made in two phases: first, the business rules are identified for the particular application is
represented in terms of general syntax. Then the rules are converted into Jess syntax, in order to
provide more flexibility when dynamic changes are made. Next, the business rules instance
requires checking whether the modification will maintain the process consistency. There are
many possible extensions of the presented work; we intend to extend the dynamic changes in
business rules.
11. References
[1] Chun Ouyang , “From Business Process Models to Process-Oriented Software Systems”
[2] Michael zur Muehlen, “Business Process and Business Rule Modeling Languages for Compliance
Management: A Representational Analysis”, Twenty-Sixth International Conference on Conceptual
Modeling - ER 2007 - Tutorials, Posters, Panels and Industrial Contributions, Auckland, New Zealand.
Figure 2. Dynamic rule Extraction

28
[3] Josef Schiefer, “Event-Driven Rules for Sensing and Responding to Business Situations”.
[4] Claire Costello, “ Orchestrating Supply chain Interactions using Emerging Process Description
Languages and Business Rules”.
[5] Anca Andreescu, “ A General Software Development Process Suitable for Explicit Manipulation of
Business Rules”
[6] Milan Milanović1, “ Modeling Service Orchestrations with a Rule-enhanced Business Process
Language”
[7] Olegas Vasilecas,” Ensuring Consistency of Information Systems Rules Models”.
[8] Anis Charfi, “ Hybrid Web Service Composition: Business Processes Meet Business Rules”.
[9] Bruno de Moura Araujo, “ A method for Validating the Compliance of Business Processes to
Business Rules”.
[10] Nicholas Zsifkov, “ Business Rules Domains and Business Rules Modeling”.
[11] Antonio Oliveira, “ Filho Change Impact Analysis from Business Rules”.
[12] Jose F. Mejia Bernal, “ Dynamic Context-Aware Business Process: A Rule-Based Approach
Supported by Pattern Identification”.
[13] Timon C. Du and Hsing-Ling Chen ,“Building a Multiple-Criteria Negotiation Support System”,
IEEE transactions on knowledge and data engineering, vol. 19, no. 6, June 2007.
[14] Sam Weber, Hoi Chan, Lou Degenaro, Judah Diament, Achille Fokoue-Nkoutche, and Isabelle
Rouvellou, “Fusion: A System For Business Users To Manage Program Variability”, IEEE Transaction
on software engineering , Nov 2008.
[15] H. M. Sneed, “Extracting Business Logic from Existing COBOL Programs as a Basis for
Redevelopment”, 9th
International Workshop on Program Comprehension, Toronto, Canada, 2001, pp.
167-175.
[16] Sangseung Kang, “Design of Rule Object Model for Business Rule Systems”, 1996,pp. 818-822.
[17] Olga Levina, “Extracting Business Logic from Business Process Models”, 2010 IEEE.
[18] Mohammed Alawairdhi, “A Business-Logic Based Framework for Evolving Software Systems”,
2009 33rd Annual IEEE International Computer Software and Applications Conference.
[19] Olegas Vasilecas, “Ensuring Consistency of Information Systems Rules Models”, the International
Multiconference on Computer Science and Information Technology, 2008.
[20] Anis Charfi, “ Hybrid Web Service Composition: Business Processes Meet Business Rules”,
ICSOC'04, November 15–19, 2004, New York, New York, USA.
[21] Jose F. Mejia Bernal, “ Dynamic Context-Aware Business Process: A Rule-Based Approach
Supported by Pattern Identification”, SAC’10, March 22-26, 2010, Sierre, Switzerland.
[22] Gulnoza Ziyaeva, Eunmi Choi, and Dugki Min, “Content-Based Intelligent Routing and Message
Processing in Enterprise Service Bus”, International Conference on Convergence and Hybrid Information
Technology, 2008
[23] en.wikipedia.org/wiki/Business_rule

29
Authors
Thirumaran. M, working as Asst.Professor in Pondicherry Engineering College,
Pondicherry, India, one of India’s premier institutions providing high quality education and a
great platform for research. He pursued his B.Tech and M.Tech in Computer Science and
Engineering from the Pondicherry University. The author is specialized in Web Services and
Business Object Model and possesses a very profound knowledge in the same. He has worked
on establishing the Business Object Model and Business Logic System with respect to Web
Service Computation, Web Service Composition and Web Service Customization. His flair for
research has made him explore deep in this domain and he has published more than 20 papers
in various International Conferences, Journals and Magazines. Currently he is working on
developing a model for Business Logic Systems for various E-Commerce systems.
Ilavarasan. E, working as Associate Professor in Pondicherry Engineering College,
Pondicherry, India. He received his Bachelor’s degree in Mathematics from the University of
Madras in the year 1987 and Master’s degree in Computer Applications in the year 1990 from
Pondicherry University. Later he completed his M.Tech., degree in Computer Science and
Engineeering at Pondicherry University in the year 1997. He has published more than Twenty
five research papers in the International Journals and Conferences. His area of specialization
includes Parallel and Distributed Systems, Design of Operating System and Web Technology.
Thanigaivel. K, studying in Pondicherry Engineering College, Pondicherry, India. He
received his B.Tech degree in Computer Science and Engineering from the Pondicherry
University in the year 2009. He currently pursuing M.Tech., degree in Computer Science and
Engineering at Pondicherry University and he is currently working in the area of Webservices.
Abarna. S, studying in Pondicherry Engineering College, Pondicherry, India. She
currently pursuing M.Tech., degree in Computer Science and Engineering at Pondicherry
University and she is currently working in the area of Webservices.

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