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Similaire à A Model Driven Reverse Engineering framework for extracting business rules out of a Java application
Similaire à A Model Driven Reverse Engineering framework for extracting business rules out of a Java application (20)
A Model Driven Reverse Engineering framework for extracting business rules out of a Java application
- 1. Valerio Cosentino - IBM, AtlanMod, INRIA & EMN, Nantes - valerio.cosentino@fr.ibm.com
Jordi Cabot - AtlanMod, INRIA & EMN, Nantes - jordi.cabot@mines-nantes.fr
Patrick Albert – IBM - albertpa@fr.ibm.com
Philippe Bauquel – IBM - bauquel.p@fr.ibm.com
Jacques Perronnet – IBM - jacques_perronnet@fr.ibm.com
A Model Driven Reverse Engineering
framework for extracting business
rules out of a Java application
1
RuleML 2012, Montpellier, France – 29 August
© 2009 IBM Corporation
- 2. Outline
Introduction
– Context & problem
– Example
– Business rule extraction process
Framework overview
– Model discovery
– Variable classification
– Business rule identification
– Business rule representation
Conclusion & Future work
2 © 2009 IBM Corporation
- 3. Introduction - context & problem
Context: every organization needs to periodically reevaluate and evolve
its company policies enforced in its Information System (IS) by means of
a set of business rules
3 © 2009 IBM Corporation
- 4. Introduction - context & problem
Context: every organization needs to periodically reevaluate and evolve
its company policies enforced in its Information System (IS) by means of
a set of business rules
Business rule:
– « Relevant action aiming at constraining some precise aspect of a
business »
– Key component for ISs
4 © 2009 IBM Corporation
- 5. Introduction - context & problem
Context: every organization needs to periodically reevaluate and evolve
its company policies enforced in its Information System (IS) by means of
a set of business rules
Business rule:
– « Relevant action aiming at constraining some precise aspect of a
business »
– Key component for ISs
Problem: policies and rules must be aligned at all time, but in most of
ISs business rules are scattered among the source code.
5 © 2009 IBM Corporation
- 6. Introduction - context & problem
Context: every organization needs to periodically reevaluate and evolve
its company policies enforced in its Information System (IS) by means of
a set of business rules
Business rule:
– « Relevant action aiming at constraining some precise aspect of a
business »
– Key component for ISs
Problem: policies and rules must be aligned at all time, but in most of
ISs business rules are scattered among the source code.
Hard to find the business rules within the IS even for small application
6 © 2009 IBM Corporation
- 7. Introduction - context & problem
Context: every organization needs to periodically reevaluate and evolve
its company policies enforced in its Information System (IS) by means of
a set of business rules
Business rule:
– « Relevant action aiming at constraining some precise aspect of a
business »
– Key component for ISs
Problem: policies and rules must be aligned at all time, but in most of
ISs business rules are scattered among the source code.
Hard to find the business rules within the IS even for small application
Hard to evolve (quickly and safely) company policies
7 © 2009 IBM Corporation
- 10. Introduction - example
Rules modeling the application:
– Hunters:
Never die
Hunt animals
– Rabbits & Birds:
Can die by being eaten by foxes, hunted by hunters, of
starvation, old age or overcrowding
Can breed when they reach their breeding age
Eat grass
– Foxes:
Can die by being eaten by hunters, of starvation, old age or
overcrowding
Can breed when they reach their breeding age
Eat rabbits and birds
10 © 2009 IBM Corporation
- 11. Introduction - example
Rules modeling the application:
– Hunters:
Never die
Hunt animals
– Rabbits & Birds:
Can die by being eaten by foxes, hunted by hunters, of
starvation, old age or overcrowding
Can breed when they reach their breeding age
Eat grass
– Foxes:
Can die by being eaten by hunters, of starvation, old age or
overcrowding
Can breed when they reach their breeding age
Eat rabbits and birds
11 © 2009 IBM Corporation
- 16. Introduction - business rule extraction process
Business rule extraction (BREX) process:
– Allows extracting business rules out of an IS, isolating the code
segments which are directly related to business
– Three major activities:
Variable Classification → finds variables related to
domain/business concepts and hintining at BRs
Business rule identification → collects chunks of code related to
the variables identified in the previous step
Business rule representation → presents the extracted BRs by
means of artifacts (graphs, textual representations, …)
16 © 2009 IBM Corporation
- 17. Introduction - business rule extraction process
Business rule extraction (BREX) process:
– Allows extracting business rules out of an IS, isolating the code
segments which are directly related to business
– Three major activities:
Variable Classification → finds variables related to
domain/business concepts and hintining at BRs
Business rule identification → collects chunks of code related to
the variables identified in the previous step
Business rule representation → presents the extracted BRs by
means of artifacts (graphs, textual representations, …)
Model Driven Engineering techniques:
– Abstract & homogeneous representation
– Modular solving process
– Non-intrusive solution
17 © 2009 IBM Corporation
- 18. Framework overview - model discovery
A new operation (Model Discovery) is added to the BRE process to
move the problem from a grammarware technological space to the
modelware one.
– Input: source code
– Output: platform specific model (PSM)
18 © 2009 IBM Corporation
- 19. Framework overview - variable classification
Variables Classification identifies the domain variables together with
their containing classes
– Input: PSM
– Output: model containing all domain's classes and their inner
variables
19 © 2009 IBM Corporation
- 26. Framework overview - variable classification - metamodel
For each class in a group, its variables are classified in:
– Single-access: class attributes occurring at most once on the left
side of an assignment
– Multi-access: class attributes occurring more than once on the left
side of an assignment
– Potentials: variables declarated in methods and occurring on the left
side of an assignment
26 © 2009 IBM Corporation
- 27. Framework overview - variable classification - metamodel
For each class in a group, its variables are classified in:
– Single-access: class attributes occurring at most once on the left
side of an assignment
– Multi-access: class attributes occurring more than once on the left
side of an assignment
– Potentials: variables declarated in methods and occurring on the left
side of an assignment
– Traceability: relates the classified variables to the source code
27 © 2009 IBM Corporation
- 29. Framework overview - business rule identification
Domain model extraction:
– Input: PSM, the domain variables model
– Output:
Model conforming to the Business Object Model/Vocabulary
[BOM/VOC] metamodel of IBM WebSphere ILOG Jrules
– Extracts method signatures and class attributes from the classes
containing the domain variables identified in the variables
classification step
– Provides a default vocabulary for these entities to be reused in the
description of the business rules
– The user can tune the process and define its verbalization
29 © 2009 IBM Corporation
- 30. Framework overview - business rule identification
Domain model extraction:
30 © 2009 IBM Corporation
- 31. Framework overview - business rule identification
Slicing operation:
– Input: PSM, a variable i contained in the domain variables model
– Output:
PSM enriched with annotations (PSMA) on all the statements,
variable declarations and methods relevant for i
31 © 2009 IBM Corporation
- 32. Framework overview - business rule identification
Slicing operation:
– Input: PSM, a variable i contained in the domain variables model
– Output:
PSM enriched with annotations (PSMA) on all the statements,
variable declarations and methods relevant for i (ex: alive)
32 © 2009 IBM Corporation
- 33. Framework overview - business rule identification
Slicing operation:
– Input: PSM, a variable i contained in the domain variables model
– Output:
PSM enriched with annotations (PSMA) on all the statements,
variable declarations and methods relevant for i
33 © 2009 IBM Corporation
- 34. Framework overview - business rule identification
Slicing operation:
– Input: PSM, a variable i contained in the domain variables model
– Output:
PSM enriched with annotations (PSMA) on all the statements,
variable declarations and methods relevant for i
34 © 2009 IBM Corporation
- 35. Framework overview - business rule identification
Slicing operation:
– Input: PSM, a variable i contained in the domain variables model
– Output:
PSM enriched with annotations (PSMA) on all the statements,
variable declarations and methods relevant for i
35 © 2009 IBM Corporation
- 36. Framework overview - business rule identification
Slicing operation:
– Input: PSM, a variable i contained in the domain variables model
– Output:
PSM enriched with annotations (PSMA) on all the statements,
variable declarations and methods relevant for i
36 © 2009 IBM Corporation
- 37. Framework overview - business rule identification
Slicing operation:
– Input: PSM, a variable i contained in the domain variables model
– Output:
PSM enriched with annotations (PSMA) on all the statements,
variable declarations and methods relevant for i
37 © 2009 IBM Corporation
- 38. Framework overview - business rule identification
Slicing operation:
– Input: PSM, a variable i contained in the domain variables model
– Output:
PSM enriched with annotations (PSMA) on all the statements,
variable declarations and methods relevant for i
38 © 2009 IBM Corporation
- 39. Framework overview - business rule identification
Slicing operation:
– Input: PSM, a variable i contained in the domain variables model
– Output:
PSM enriched with annotations (PSMA) on all the statements,
variable declarations and methods relevant for i
39 © 2009 IBM Corporation
- 53. Framework overview - business rule identification
Business rules model extraction:
53 © 2009 IBM Corporation
- 54. Framework overview - business rule identification
Business rules model extraction:
– Input: Domain model and PSM enriched with annotations (PSMA) on
all the statements, variable declarations and methods relevant for i
– Output:
Business rule model for the variable i
– PSMA contains information of classes outside the business domain.
The domain model is used to exclude them
54 © 2009 IBM Corporation
- 55. Framework overview - business rule identification
Classes related to the variable alive:
55 © 2009 IBM Corporation
- 56. Framework overview - business rule identification
Classes outside the domain:
56 © 2009 IBM Corporation
- 57. Framework overview - business rule identification
Classes inside the domain:
57 © 2009 IBM Corporation
- 58. Framework overview - business rule identification
Intersection with the domain classes:
58 © 2009 IBM Corporation
- 61. Framework overview
Business rules representation:
Business rules representation provides human-understandable artifacts
(text and graph) for the extracted BRs.
– Input: domain model (optional), business rule model-i
– Output: text or graph
61 © 2009 IBM Corporation
- 64. Conclusion & Future work
MDE benefits:
– Non-intrusive approach
– Modular framework
– Internal/external representation of BRs
– Traceability
Test on a real use case:
– IBM Rational Programming Patterns :
> 5000 classes, 476 system variables
Variable classification step improved with new heuristics
Optimization of the slicing operation
Future works:
– Extend the framework to other languages
– Identify BRs in the other layers composing an application
64 © 2009 IBM Corporation