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Business Rules and Business Processes - How good partners are they?

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Business process modeling is commonly used in development of large scale enterprise systems. The previous research on this topic demonstrated that process-oriented models might be too rigid for dynamic adaptations of the business logic. Rule-based approaches are considered an alternative, which offers more flexibility thanks to the declarative nature of rules and their underlying reasoning algorithms. However, modeling a business process exclusively through rules is a tedious process for developers in terms of the overall business process comprehension. A solution "in-between" is to have a modeling approach that integrates both rule- and process-oriented modeling perspectives. In this talk, we will discuss the experience gained in the development of and work with rBPMN (rule-based BPMN), a language based on the integration of Business Process Modeling Notation (BPMN) with the REWERSE Rule Markup Language. After a brief description of some key decisions made in the development of rBPMN, we will discuss experience in using rBPMN to model workflow patterns, service-interaction patterns, message-exchange patterns, and a recently identified group of patterns for integration rules into business processes. Finally, the talk will discuss some open research challenges in the area such as capturing business knowledge, usability of business modeling languages, and methods for configuration of business processes.

Published in: Technology, Business
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Business Rules and Business Processes - How good partners are they?

  1. 1. Business Rules and Business Processes How good partners are they? Dragan Gašević
  2. 2. Business processes Many (buzz)words Dynamic Variable ChangeableFlexible Configurable Declarative Agile
  3. 3. What’s all this about?  Perhaps “A business process is flexible if possible to change it without replacing it completely.” Rainer Schmidt, Gil Regev, Pnina Soffer, Guest Editorial: Requirements for Flexibility and the Ways to Achieve It, Int. J. Business Process Integration and Management, Vol. 3, No. 1, 2008, pp. 1-4
  4. 4. Now, please, help!  What’s different and similar? Business processesDynamic Variable ChangeableFlexible Configurable Declarative Agile
  5. 5. The rest of the talk  A perspective to the problem  A language development experience  Open challenges
  6. 6. Part I A Perspective to the Problem
  7. 7. Let me introduce myself Also, an excuse to invite you to the 4th International Conference on Software Language Engineering http://planet-sl.org/sle2011
  8. 8. Why not maintainability?!  Already known in (software) engineering  … the ease with which a product can be maintained to  correct defects  meet new requirements  make future maintenance easier, or  cope with a changed environment As simple as a Wikipedia entry: http://en.wikipedia.org/wiki/Maintainability
  9. 9. Software Quality  Maintainability characteristics  Analyzability  capability to be diagnosed for deficiency  Changeability  possibility and ease of change when modifications needed  Understandability  prospect and likelihood to be understood & comprehended ISO 9126 standard, Software engineering — Product quality
  10. 10. Community Engineering
  11. 11. Changeability in BPs Possibility and ease of change when modifications needed
  12. 12. Business Processes  Excerpts of a definition [Weske, 2007]  Coordinated set of activities  Business goals  Perspectives  Control flow, data flow, interaction, …
  13. 13. Business Rules  Excepts of a definition [BRG, 2009]  define or constrain some aspects  assert business structure or control or influence the behavior  Types [Wanger, 2005]  Derivation, integrity, production, & reaction
  14. 14. Processes & rules  Complete processes modeled by rules  With reaction and production rules  Some issues  What’s the identity of a business process?  Which languages to use?  Are the languages at the same level?
  15. 15. Processes & rules  Hybrid approaches  BP stays, but rules are added for  control flow decisions, data constraints, and process composition [Graml et al., 2007]
  16. 16. Part II Language Development Experience What else to expect from a ?!
  17. 17. Objective A systematic definition of a rule-based business modeling language
  18. 18. rBPMN – Rule-enhanced BPMN  Model-driven engineering approach  Language engineering with metamodeling  Business process and rule (meta)models  Integration on the level of the metamodels  Validity of expressions in models  Integration of BPMN and R2ML languages EDOC 2009
  19. 19. Challenges  to have rules as first class concepts in BPs  to support vocabularies/ontologies  to define message typing  to formalize defining conditions  to enable declarative (parts of) processes MODELS 2009
  20. 20. MODELS 2009 BPMN Language The current BPMN2 metamodel submission
  21. 21.  REWERSE I1 Rule Markup Language (R2ML)  with a UML-based graphical concrete syntax MODELS 2009 Rule Modeling
  22. 22. MODELS 2009
  23. 23. rBPMN in Action
  24. 24. rBPMN in Action
  25. 25. rBPMN in Action OWL-based reasoning
  26. 26. rBPMN in Action Rete-based
  27. 27. Modeling Perspectives  Orchestrations – CASCON 2010  Choreographies – EDOC 2010
  28. 28. Workflow Patterns  Milestone pattern
  29. 29. Book Request Scenario
  30. 30. Pattern group Pattern Business process modeling language UML BPEL BPMN AORML rBPMNBasiccontrol- flow Sequence + + + + + Parallel Split + + + + + Synchronization + + + + + Exclusive Choice + + + + + Simple Merge + + + + + Advanced branchingand synchronizati on Multi Choice - + - + + Multi Merge - - +/- + + Discriminator - - - +/- + Synchronizing Merge - + + - + Struct ural Arbitrary Cycles + - + + + Implicit Termination + + + + + Multiple Instances MI without synchronization + + + + + MI with a Priori Design Time Knowledge + + + + + MI with a Priori Runtime Knowledge + - - + + MI without a Priori Runtime Knowledge - - - + + State- based Deferred Choice + + + + + Interleaved Parallel Routing - +/- +/- - +/- Milestone - - - - + Cancellati on Cancel Activity + + + + + Cancel Case + + + + +
  31. 31.  Multiplicity of participants |||  References  to distinguish participants  Correlation information  who sent a message MODELS 2009 Interaction Models
  32. 32. MODELS 2009 Service Interaction  Contingent requests pattern
  33. 33. MODELS 2009 Service Interaction  Contingent requests pattern
  34. 34. Language Pattern group Pattern Let’s Dance BPMN WS- CDL iBPMN rBPMN Send + + + + + Receive + + + + +1) Send/Receive + + + + + Racing incoming messages + + + + + One-to-many send + - +/- + + One-from-many receive + - + + + 2) One-to-many send/receive + - +/- + + Multi-responses + + + + + Contingent requests +/- - +/- +/- +3) Atomic multicast notification - - - - - Request with referral + - + + + Relayed request + - + + +4) Dynamic routing - - +/- - +/-
  35. 35. rBPMN Editor  Going out as open source shortly  Binaries available for download and use  Looking fwd to your feedback  http://code.google.com/p/rbpmneditor/
  36. 36. rBPMN Heroes  Language design and implementation Milan Milanovic Luis Rocha
  37. 37. Demo http://code.google.com/p/rbpmneditor/
  38. 38. rBPMN Analysis  Representational analysis of BPMN  Based on the BWW model Constructs Percentage Constructs Percentage Constructs Percentage Constructs Percentage Completeness 17 60.7% 17 60.7% 18 64.3% 19 67.9% Deficit 11 39.3% 11 39.3% 10 35.7% 9 32.1% Redundancy 11 39.3% 11 39.3% 16 57.1% 16 57.1% Overload 5 17.9% 5 17.9% 29 103.6% 30 107.1% Excess 4 14.3% 5 17.9% 16 57.1% 22 78.6% BPMN 1.2 Core BPMN 2.0 Core BPMN 1.2 Ext BPMN 2.0 Ext Vid Prezel rBPMN hero
  39. 39. rBPMN Expressiveness  Construct deficit
  40. 40. rBPMN Expressiveness  Cluster by cluster comparison
  41. 41. rBPMN Expressiveness  Overlap analysis PΔR - Symmetric Difference; P R – Intersection; P/R & R/P -Relative Complement∩
  42. 42. Part III Open Challenges
  43. 43. Language Issues  Change propagation  Traceability  Consistency  Semantics  Static and operational
  44. 44. http://code.google.com/p/twouse/
  45. 45. Using ontologies Not only OWL-based reasoning
  46. 46. General vs. Specific Why not to use DSLs instead?!
  47. 47. More or less rules!? Methodologies, yes! Empirical research even more!
  48. 48. Quality Issues  Usability  Natural language vs. visual  Physics of notation, cognitive dimensions, …  Maintainability  Understandability, changeability, analyzability  Internal structure metrics and experiments  …
  49. 49. Community call: We need a corpus!
  50. 50. Which method to use? Theoretical Case study Empirical Action research Ethnography Simulation Scenario analysis Systemic observation Pilot testing Grounded theory Critical analysis of literature Expert review Focus group Algorithmic analysis Assertion Cognitive walkthrough Concept mapping Contextual inquiry Design research End-user studyExploratory data analysis Heuristic evaluation Lessons learned
  51. 51. Community Engineering Pioneer in bridging
  52. 52. Organizational issues  Motivating for knowledge externalization  Organizational learning  Inter-organizational affairs
  53. 53. Acknowledgements  Milan Milanovic, Luis Rocha, Vid Prezel  Gerd Wagner and Adrian Giurca – rBPMN  Jean-Marie Favre and Ralf Lämmel – SLE  Lab for Semantic Technologies  Marek Hatala, Ebrahim Bagheri, Marko Boskovic, Amal Zouaq,Bardia Mohabbati, Mohsen Asadi, Ivana Ognjanovic, Samaneh Soltani, Toni Lenihan
  54. 54. Thank you! Questions?

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