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

8. Introduction - example
8 © 2009 IBM Corporation

9. Introduction - example
9 © 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

12. Introduction – example
12 © 2009 IBM Corporation

13. Introduction - example
13 © 2009 IBM Corporation

14. Introduction - example
14 © 2009 IBM Corporation

15. Introduction - example
15 © 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

20. Framework overview - variable classification
20 © 2009 IBM Corporation

21. Framework overview - variable classification
21 © 2009 IBM Corporation

22. Framework overview - variable classification
22 © 2009 IBM Corporation

23. Framework overview - variable classification
23 © 2009 IBM Corporation

24. Framework overview - variable classification
24 © 2009 IBM Corporation

25. Framework overview - variable classification
25 © 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

28. Framework overview - business rule identification
28 © 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

40. Framework overview - business rule identification
40 © 2009 IBM Corporation

41. Framework overview - business rule identification
41 © 2009 IBM Corporation

42. Framework overview - business rule identification
42 © 2009 IBM Corporation

43. Framework overview - business rule identification
43 © 2009 IBM Corporation

44. Framework overview - business rule identification
44 © 2009 IBM Corporation

45. Framework overview - business rule identification
45 © 2009 IBM Corporation

46. Framework overview - business rule identification
46 © 2009 IBM Corporation

47. Framework overview - business rule identification
47 © 2009 IBM Corporation

48. Framework overview - business rule identification
48 © 2009 IBM Corporation

49. Framework overview - business rule identification
49 © 2009 IBM Corporation

50. Framework overview - business rule identification
50 © 2009 IBM Corporation

51. Framework overview - business rule identification
51 © 2009 IBM Corporation

52. Framework overview - business rule identification
52 © 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

59. Framework overview - business rule identification - metamodel
59 © 2009 IBM Corporation

60. Framework overview - business rule identification - metamodel
60 © 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

62. Framework overview
 Text:
62 © 2009 IBM Corporation

63. Framework overview
 Graph:
63 © 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

65. Questions
65 © 2009 IBM Corporation