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Repairing Process Models to Match Reality

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Presentation on repairing process models to conform to observed process executions, given at BPM 2012 in Tallinn, Estonia, September 2012.

Publié dans : Technologie, Business
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Repairing Process Models to Match Reality

  1. 1. Dirk Fahland Wil van der AalstRepairing Process Models
  2. 2. Situation: model vs. reality process model Conformance Check Is this a good model for the real process? event log PAGE 1
  3. 3. Discovery vs. Repair original Whyrepaired processdiscovered not use discovery? PAGE 2
  4. 4. Problem Statement repaired process repair process model model Conformance Check Is this a good model for the real process? event log PAGE 3
  5. 5. Conformance process model fitness precision model can model behavior replay the log close to the log generalization simplicity event log model is as simple model allows more than as possible just the log PAGE 4
  6. 6. Here: focus on fitness process model fitness precision preserve during repair post-processing [Fahland, Aalst, BPM2011] generalization simplicity event log pre-process log (filter noise, etc.) PAGE 5
  7. 7. Problem Analysis repaired process repair process model model fitness replays all traces repaired discoveredreplays some traces original model distance to original model PAGE 6
  8. 8. Approach to Model Repair repaired process remove process model non-required model conformance deviations checker add missing event log PAGE 7
  9. 9. Approach to Model Repair repaired process remove process model non-required model conformance deviations checker add missing event log PAGE 8
  10. 10. Align Log and Model p2 p4 p1 Bmodel: A p3 p5 E p6 C DABFBDCE log PAGE 9
  11. 11. Align Log and Model p2 p4 p1 Bmodel: A p3 p5 E p6 C DABFBDCE log alignment PAGE 10
  12. 12. Align: Synchronous Move on A p2 p4 p1 Bmodel: A p3 p5 E p6 C D AABFBDCE A p2 p3 log alignment PAGE 11
  13. 13. Align: Synchronous Move on B p2 p4 p1 Bmodel: A p3 p5 E p6 C D A BABFBDCE A B p2 p4 p3 p3 log alignment PAGE 12
  14. 14. Align: Log Move on F p2 p4 p1 Bmodel: A p3 p5 E p6 C D A BABFBDCE A B F p2 p4 p3 p3 log alignment PAGE 13
  15. 15. Align: Log Move on B p2 p4 p1 Bmodel: A p3 p5 E p6 C D A BABFBDCE A B F B p2 p4 p3 p3 log alignment PAGE 14
  16. 16. Align: Model Move on C p2 p4 p1 Bmodel: A p3 p5 E p6 C D A B CABFBDCE A B F B p2 p4 p4 p3 p3 p5 log alignment PAGE 15
  17. 17. Align: Synchronous Move on D p2 p4 p1 Bmodel: A p3 p5 E p6 C D A B C DABFBDCE A B F B D p2 p4 p4 p4 p3 p3 p5 p3 log alignment PAGE 16
  18. 18. Align: Synchronous Move on C p2 p4 p1 Bmodel: A p3 p5 E p6 C D A B C D CABFBDCE A B F B D C p2 p4 p4 p4 p4 p3 p3 p5 p3 p5 log alignment PAGE 17
  19. 19. Align: Synchronous Move on E p2 p4 p1 Bmodel: A p3 p5 E p6 C D A B C D C EABFBDCE A B F B D E p2 p4 p4 p4 p4 p6 p3 p3 p5 p3 p5 log alignment PAGE 18
  20. 20. Complete Alignment p2 p4 p1 Bmodel: A p3 p5 E p6 C D A B C D C E firing sequenceABFBDCE A B F B D C E trace p2 p4 p4 p4 p4 p6 visited markings p3 p3 p5 p3 p5 of the model log alignment PAGE 19
  21. 21. Diagnostic Information FB sublog @ {p4,p3} need to replay FBwhen in marking {p4,p3} need to skip C to replay trace A B C D C E firing sequence A B F B D C E trace p2 p4 p4 p4 p4 p6 visited markings p3 p3 p5 p3 p5 of the model PAGE 20
  22. 22. Approach to Model Repair repaired process make optional / process model remove model activities that have to be skipped/removed conformance add checker subprocesses discover discover event log sublogs of events that cannot be replayed PAGE 21
  23. 23. Sublogs: Join by Events and Location p2 p4 p1 B A p3 p5 E p6 C D GH @ {p2,p3} FB @ {p4,p3}conformance checker GH @ {p4,p3} BF @ {p4,p5} sublogs @ locations PAGE 22
  24. 24. Sublogs: Join by Events and Location p2 p4 p1 B A p3 p5 E p6 C D GH FB @ {p3} @ {p4} GH BF sublogs @ locations PAGE 23
  25. 25. Sublog of Events  Add Subprocess B p2 p4 F p1 B A p3 p5 E p6 C D GH FB @ {p3} @ {p4} GH BF PAGE 24
  26. 26. Sublog of Events  Add Subprocess B p2 p4 F p1 B A p3 p5 E p6 C D H G GH FB @ {p3} @ {p4} GH BF PAGE 25
  27. 27. Events to Skip B p2 p4 F p1 B A p3 p5 E p6 C D H G allow to skip Cconformance checker PAGE 26
  28. 28. Events to Skip B p2 p4 F p1 B A p3 p5 E p6 C D H G allow to skip Cconformance checker PAGE 27
  29. 29. Approach to Model Repair repaired process make optional / process model remove model activities that have to be skipped/removed conformance add checker subprocesses discover discover event log sublogs of events that cannot be replayed PAGE 28
  30. 30. Implemented: ProM > Uma > Repair Model municipality process + log model moves: 3327 log moves: 310 deviations per trace: 2-49 PAGE 29
  31. 31. Implemented: ProM > Uma > Repair Model municipality process + log model moves: 3327 log moves: 310 deviations per trace: 2-49 PAGE 30
  32. 32. Implemented: ProM > Uma > Repair Model municipality process + log model moves: 3327 log moves: 310 deviations per trace: 2-49 PAGE 31
  33. 33. Implemented: ProM > Uma > Repair Model municipality process + log (filtered) model moves: 681 log moves: 229 deviations per trace: 1-12 PAGE 32
  34. 34. Implemented: ProM > Uma > Repair Model municipality process + log (filtered) model moves: 681 log moves: 229 deviations per trace: 1-12 PAGE 33
  35. 35. Implemented: ProM > Uma > Repair Model PAGE 34
  36. 36. Implemented: ProM > Uma > Repair Model PAGE 35
  37. 37. Case Study: Deviations vs. Similarity distance to original [Dijkman et al., BPM 2009] 1 reference model 1 10 logs .8 • 180-481 traces, up to 82 events per trace .6 • 2-49 deviations per trace rediscovered .4 + simplified results • distance to original < .2 .2 • better than rediscovery repaired • stable in # of deviations 0 2 4 6 8 10 12 avg. deviations per trace PAGE 36
  38. 38. Conclusion: new tool in the box PAGE 37
  39. 39. Conclusion effective technique for model repair • alignment  sublogs of missing events  subprocess future work: • quality of alignment  quality of repair • allow to change ordering of tasks • repair for precision, generalization, … • many more … PAGE 38
  40. 40. Dirk Fahland Wil van der AalstRepairing Process Models
  41. 41. Conformance 4 quality measures process model fitness precision “flower model can model” behavior replay the log not explained by log is small generalization simplicity event log model is as simple model allows more than as possible just the log PAGE 40
  42. 42. Conformance 4 quality measures process model fitness precision “each trace model can separately” behavior replay the log not explained by log is small generalization simplicity event log model is as simple model allows more than as possible just the log PAGE 41
  43. 43. Conformance 4 quality measures process model fitness “spaghetti” precision model can behavior replay the log not explained by log is small generalization simplicity event log model is as simple model allows more than as possible just the log PAGE 42

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