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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
Extracting Business Rules from COBOL:
A Model-Based Framework
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WCRE 2013, Koblenz, Germany – 14-17 October
© 2009 IBM Corporation

2. Outline
 Introduction
– Problem
– Running example
 Framework overview
– Model Discovery
– Business Term Identification
– Business Rule Identification
– Business Rule Representation
 Early validation
 Conclusion & future work
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3. Problem
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4. Problem
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5. Problem
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6. Problem
 Poor/outdated system documentation
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7. Problem
 Poor/outdated system documentation
 The original developers/business analysts may have left the
organization
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8. Problem
 Poor/outdated system documentation
 The original developers/business analysts may have left the
organization
 Business rules spread in the source code
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9. Problem
 Understanding and evolving the business policies together with
the corresponding business rules is not trivial
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10. Problem
 Understanding and evolving the business policies together with
the corresponding business rules is not trivial
 Specially true for legacy systems
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11. COBOL
 Largely used:
– 200 billion lines of code in existence
– 70%-75% of business and transaction systems
– 90% of global financial transactions
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© 2009 IBM Corporation

12. COBOL
 Largely used:
– 200 billion lines of code in existence
– 70%-75% of business and transaction systems
– 90% of global financial transactions
 Shortage of COBOL developers:
– Study on 357 Information Technology professionals
– 46% says they already notice a shortage
– 50% says the average age is > 45
– 22% says the age is > 55
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13. Running example
Need
Bag
Money
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Is open
Quantity
Price
Business rules in the program:
–If the shop is open, then the customer can buy products
–If a product P is needed, then the customer buys P
–If the client has enough money, then he can buy products
–If the client has enough room in his bag, he can buy products
–If a product is available, then it may be bought
–If a product is bought, its quantity is decreased by one
© 2009 IBM Corporation

14. Running example
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Rule embedded in the code:
 if a product is bought, its quantity is decreased by one
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15. Running example

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Rule embedded in the code:
 if a product is bought, its quantity is decreased by one
© 2009 IBM Corporation

16. Running example

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Rule embedded in the code:
 if a product is bought, its quantity is decreased by one
© 2009 IBM Corporation

17. Running example
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Rule embedded in the code:
 if a product is bought, its quantity is decreased by one
© 2009 IBM Corporation

18. Framework overview
 Model Driven Engineering:
– Modular framework
– Internal/external representation of BRs
– Traceability between rules and source code
– Mature tools available for model manipulations, visualizations
and transformations (e.g., ATL, Xtext, ...)
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19. COBOL Model Discovery
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20. Business Term Identification
 Manually: the user selects the variables
 Automatically: heuristic-based strategy
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21. Business Term Identification
 Manually: the user selects the variables
 Automatically: heuristic-based strategy
1) Statements are separated in groups:
– Conditional
– Computational
– ...
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22. Business Term Identification
 Manually: the user selects the variables
 Automatically: heuristic-based strategy
1) Statements are separated in groups:
– Conditional
– Computational
– ...
2) Variables in statements are classified in:
– Condition
– Index
– Source
– Target
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23. Business Term Identification
 Manually: the user selects the variables
 Automatically: heuristic-based strategy
– all target variables in computational statements
– all variables in conditional statements
– ...
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24. Business Rule Identification
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25. Business Rule Identification – Rule Discovery
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Rule Fragment Identification:
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26. Business Rule Identification – Rule Discovery
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Rule Fragment Identification:
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27. Business Rule Identification – Rule Discovery
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Rule Fragment Identification:
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28. Business Rule Identification – Rule Discovery
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Rule Context Identification:
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29. Business Rule Representation
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30. Business Rule Representation – Vocabulary Extraction
 Optional and manual step
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31. Business Rule Representation – Visualization
 Text-based visualization
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32. Business Rule Representation – Visualization
 Text-based visualization
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33. Business Rule Representation – Visualization
 Graph-based visualization
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34. Business Rule Representation – Visualization
 Graph-based visualization
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35. Business Rule Representation – Visualization
 Graph-based visualization
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36. Early validation
 Does the framework find complete business rules?
 Are the extracted rules understandable?
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37. Early validation
 Does the framework find complete business rules?
 Are the extracted rules understandable?
 Analysis of an IBM COBOL application:
– 14 programs
– 130 variables
– 6500 lines of code
 4 internal IBM COBOL experts:
– They knew the application
– They analysed the business rules generated by our framework
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© 2009 IBM Corporation

38. Early validation
 Does the framework find complete business rules?
 Are the extracted rules understandable?
 Analysis of an IBM COBOL application:
– 14 programs
– 130 variables
– 6500 lines of code
 4 internal IBM COBOL experts:
– They knew the application
– They analysed the business rules generated by our framework
 The framework is able to identify the complete business rules
– But some extracted rules include technical knowledge
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39. Conclusion and future work
 MDE benefits:
– Modular framework
– Internal/external representation of BRs
– Traceability between rules and source code
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40. Conclusion and future work
 MDE benefits:
– Modular framework
– Internal/external representation of BRs
– Traceability between rules and source code
 Future work:
– Complete the early validation on a real system
– Extract and unify the rules buried in other layers (presentation,
data, logic)
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41. Questions
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© 2009 IBM Corporation