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DecSerFlow Towards a Truly Declarative Service Flow Language

DecSerFlow Towards a Truly Declarative Service Flow Language. Invited talk 3rd International Workshop on Web Services and Formal Methods 8 September 2006, Vienna, Austria. Wil van der Aalst & Maja Pesic Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands

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DecSerFlow Towards a Truly Declarative Service Flow Language

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  1. DecSerFlowTowards a Truly Declarative Service Flow Language Invited talk 3rd International Workshop onWeb Services and Formal Methods8 September 2006, Vienna, Austria Wil van der Aalst & Maja Pesic Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands w.m.p.v.d.aalst@tue.nl

  2. Outline • Classical approaches • BPEL2PN • PN2BPEL • DecSerFlow • Language • Graphical notation and LTL semantics • Implementation and application (specification and enactment) • Using DecSerFlow for process mining • Conclusion

  3. Classical approaches BPEL2PN PN2BPEL • Formal languages (Petri nets, LTS, YAWL) • Graphical languages(BPMN,UML-AD) • Industry standards: • BPEL • (abstract) BPEL • WS-CDL • etc.

  4. BPEL2PN • Many translations are available, cf. • S. Hinz, K. Schmidt, and C. Stahl. Transforming BPEL to Petri nets. BPM 2005. • C. Stahl. A Petri net semantics for BPEL. Technical Report 188, Humboldt Universität zu Berlin, June 2005. • etc. • C. Ouyang, W.M.P. van der Aalst, S. Breutel, M. Dumas, A.H.M. ter Hofstede, and H.M.W. Verbeek. Formal semantics and analysis of control flow in WS-BPEL. Technical Report BPM-05-13, BPMcenter.org, June 2005. • Focus on analysis, i.e., verification of various properties. • Our approach is implemented in BPEL2PNML and WofBPEL. • cf. BEST (Berlin-Eindhoven Service Technology) program also involving tools such as BPEL2PN, LOLA and FIONA

  5. Example

  6. Corresponding Petri net

  7. PN2BPEL • Joint work with Kristian Bisgaard Lassen. • Few people have been working on this. • Purpose: Generating readable BPEL code (otherwise it has no purpose). • Implemented in WorkflowNet2BPEL4WS and ProM. • Not complete, but extendible. • Work with Chun Ouyang, Marlon Dumas, et al. (QUT) on using concepts in context of BPMN.

  8. Basic idea • Discover WF-net like components. • Look for specific patterns that can easily be mapped onto BPEL (sequence, pick, switch, while, flow, etc.). • Allow for ad-hoc extensions and re-use these.

  9. 4 types: PP, TP, PT, and TT components

  10. Sequence

  11. Flow • acyclic • explicit choice • well-structured

  12. Example

  13. Fold sequence

  14. Fold switch

  15. Fold sequence

  16. Fold sequence (2x) and pick (2x)

  17. Final step: fold flow

  18. Tool support: WorkflowNet2BPEL4WS and ProM

  19. Empirical case study: 100 Protos • Different student projects. • Size of models: 23.66 places and 26.54 transitions. • Reductions:

  20. DecSerFlowTowards a Truly Declarative Service Flow Language joint work with Maja Pesic (TU/e)

  21. Problems • Tendency to over-specify. • Focus on execution rather than "contractual" side. Proposal • A more declarative approach • Graphical • Executable • Analysis support (both design and run-time)

  22. Basic idea LTL semantics DecSerFlow notation

  23. LTL

  24. Small example

  25. 1. Existence formulas

  26. 2. Relation formulas

  27. OK: [ ] [A,B,C,D,E] [A,A,A,C,D,E,B,B,B] [B,B,A,A,C,D,E] [B,C,D,E] NOK [A] [A,A,C,D,E] Example: "existence response"

  28. Example: "response" • OK: • [ ] • [A,B,C,D,E] • [A,A,A,B,C,D,E] • [B,B,A,A,B,C,D,E] • [B,C,D,E] • NOK • [A] • [B,B,B,B,A,A]

  29. Example: "precedence" • OK: • [ ] • [A,B,C,D,E] • [A,A,A,C,D,E,B,B,B] • [A,A,C,D,E] • NOK • [B] • [B,A,C,D,E]

  30. Combinations co-existence succession

  31. 3. Negation formulas

  32. Example: "neg succession" • Not the logical negation! • OK: • [ ] • [A,C,D,E] • [A,A,A,C,D,E] • [B,B,A,A,C,D,E] • [B,C,D,E] • NOK • [A,B] • [B,A,A,C,D,E,B] or

  33. Using DecSerFlow • Nature of model: • Global model (choreography model), i.e., interactions are described from the viewpoint of an external observer who oversees all interactions between all services (non-executable specification of a contractual nature). • Local model, i.e., the DecSerFlow model is used to specify, implement, or configure a particular service. • Use: • Analysis of both global and local models. • Comparing global and local models. • Monitoring global and local models (conformance). • Enactment of local models.

  34. Enactment • A Büchi automaton typically assumes traces infinitely visiting an accepting state. There are several ways to address this. We use the approach proposed by Dimitra Giannakopoulou and Klaus Havelund to check finite traces. • We can color the constraints green (in accepting state), yellow (accepting state can still be reached), or red (accepting state cannot be reached anymore).

  35. Implementation (ConDec) • Implementation on top of YAWL and ProM. • Editor (with facilities to extend language) has been implemented. • Initial experiments with enactment service. • Plans to link editor with LTL checker in ProM.

  36. Editor Add your own constraints!

  37. Using DecSerFlow for process mining Thanks to Ton Weijters, Boudewijn van Dongen, Ana Karla Alves de Medeiros, Anne Rozinat, Christian Günter, Eric Verbeek, Ronny Mans, Minseok Song, Laura Maruster, Huub de Beer, Peter van den Brand, Jan Mendling, Andriy Nikolov, Jianmin Wang, Lijie Wen, Irene Vanderfeesten, Mariska Netjes, Steffi Rinderle, Walid Gaaloul, Gianluigi Greco, Antonella Guzzo, Maja Pesic, etc. etc.

  38. Overview: Process mining

  39. Based on an event log a model is constructed without a-priori information. Not just the control-flow, cf. the social network miner. ProM examples: alpha algorithm, heuristics miner, multi-phase miner, genetic miner, etc. Discovery DecSerFlow

  40. Alpha miner

  41. Other examples Export to CPN Tools, PNML, ARIS, EPC Tools, YAWL, Netminer, etc.

  42. The log is compare with some a-priori model, the model can be a Petri net, EPC, data model, logical/temporal property, etc. ProM examples: conformance checker and LTL checker Conformance DecSerFlow

  43. Examples

  44. An existing model is enriched with additional knowledge extracted from log. ProM examples: decision miner, staff assignment miner, performance analyzer, etc. Extension DecSerFlow

  45. Examples Export to CPN Tools!

  46. Conformancein webservices in a classical setting(abstract BPEL + SOAP messages)

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