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Reduction techniques for efficient behavioral model checking in adaptive case management

Published:03 April 2017Publication History

ABSTRACT

Case models in Adaptive Case Management (ACM) are business process models ranging from unstructured over semi-structured to structured process models. Due to this versatility, both industry and academia show growing interest in this approach. This paper discusses a model checking approach for the behavioral verification of ACM case models. To counteract the high computational demands of model checking techniques, our approach includes state space reduction techniques as a preprocessing step before state-transition system generation. Consequently, the problem size is decreased, which decreases the computational demands needed by the subsequent model checking as well. An evaluation of the approach with a large set of LTL specifications on two real-world case models, which are representative for semi-structured and structured process models and realistic in size, shows an acceptable performance of the proposed approach.

References

  1. Property Pattern Mappings for LTL. http://patterns.projects.cis.ksu.edu/documentation/patterns/ltl.shtml. Last accessed: December 1, 2016.Google ScholarGoogle Scholar
  2. A. Awad, G. Decker, and M. Weske. BPM, Milan, Italy, chapter Efficient Compliance Checking Using BPMN-Q and Temporal Logic, pages 326--341. Springer, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. A. Cimatti, E. Clarke, F. Giunchiglia, and M. Roveri. Nusmv: a new symbolic model checker. International Journal on Software Tools for Technology Transfer, 2, 2000. Google ScholarGoogle ScholarCross RefCross Ref
  4. E. M. Clarke. The Birth of Model Checking, pages 1--26. Springer, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. C. Czepa, H. Tran, U. Zdun, S. Rinderle-Ma, T. Tran, E. Weiss, and C. Ruhsam. Supporting structural consistency checking in adaptive case management. In CoopIS'15, pages 311--319, October 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. M. B. Dwyer, G. S. Avrunin, and J. C. Corbett. Patterns in property specifications for finite-state verification. In ICSE'99, pages 411--420. ACM, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. A. Elgammal, O. Turetken, W.-J. van den Heuvel, and M. Papazoglou. Formalizing and appling compliance patterns for business process compliance. Software & Systems Modeling, 15(1):119--146, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. R. Eshuis. Symbolic model checking of uml activity diagrams. ACM Trans. Softw. Eng. Methodol., 15(1):1--38, Jan. 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Forrester Research. The Forrester WaveTM: Dynamic Case Management, Q1 2016.Google ScholarGoogle Scholar
  10. P. Gonzalez, A. Griesmayer, and A. Lomuscio. Verifying gsm-based business artifacts. ICWS '12, pages 25--32. IEEE Computer Society, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. N. Herzberg, K. Kirchner, and M. Weske. Modeling and Monitoring Variability in Hospital Treatments: A Scenario Using CMMN, pages 3--15. Springer, Cham, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  12. R. Hull, E. Damaggio, F. Fournier, M. Gupta, F. T. Heath, III, S. Hobson, M. Linehan, S. Maradugu, A. Nigam, P. Sukaviriya, and R. Vaculin. Introducing the guard-stage-milestone approach for specifying business entity lifecycles. In WS-FM'10, pages 1--24. Springer, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. O. Kherbouche, A. Ahmad, and H. Basson. Using model checking to control the structural errors in bpmn models. In RCIS'13, pages 1--12, May 2013. Google ScholarGoogle ScholarCross RefCross Ref
  14. J. Koehler, G. Tirenni, and S. Kumaran. From business process model to consistent implementation: a case for formal verification methods. In EDOC'02, pages 96--106, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. M. Kurz, W. Schmidt, A. Fleischmann, and M. Lederer. Leveraging cmmn for acm: Examining the applicability of a new omg standard for adaptive case management. S-BPM ONE '15, pages 4:1--4:9. ACM, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. L. T. Ly, F. M. Maggi, M. Montali, S. Rinderle-Ma, and W. M. van der Aalst. Compliance monitoring in business processes: Functionalities, application, and tool-support. Information Systems, 54:209 -- 234, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. M. A. Marin, M. Hauder, and F. Matthes. Case management: An evaluation of existing approaches for knowledge-intensive processes. In AdaptiveCM'15, August 2015.Google ScholarGoogle Scholar
  18. A. Nigam and N. S. Caswell. Business artifacts: An approach to operational specification. IBM Syst. J., 42(3):428--445, July 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. OMG. Case Management Model and Notation (CMMN) Version 1.0. http://www.omg.org/spec/CMMN/1.0/PDF. Last accessed: December 1, 2016.Google ScholarGoogle Scholar
  20. M. Pesic and W. M. P. van der Aalst. A declarative approach for flexible business processes management. In BPM Workshops, BPM'06, pages 169--180, Berlin, Heidelberg, 2006. Springer-Verlag. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. I. Raedts, M. Petković, Y. S. Usenko, J. M. van der Werf, J. F. Groote, and L. Somers. Transformation of BPMN models for Behaviour Analysis. In MSVVEIS, pages 126--137. INSTICC press, 2007.Google ScholarGoogle Scholar
  22. Z. Sbai, A. Missaoui, K. Barkaoui, and R. Ben Ayed. On the verification of business processes by model checking techniques. In ICSTE'10, volume 1, pages V1--97--V1--103, Oct 2010. Google ScholarGoogle ScholarCross RefCross Ref
  23. A. P. Sistla and E. M. Clarke. The complexity of propositional linear temporal logics. J. ACM, 32(3):733--749, July 1985. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. D. Solomakhin, M. Montali, and S. Tessaris. Formalizing guard-stage-milestone meta-models as data-centric dynamic systems. Technical Report KRDB12-4, Free University of Bozen-Bolzano, 2012.Google ScholarGoogle Scholar
  25. K. D. Swenson, P. Nathaniel, M. J. Pucher, C. Webster, and A. Manuel. How Knowledge Workers Get Things Done, pages 155--164. Future Strategies Inc., 2012.Google ScholarGoogle Scholar
  26. W. M. P. van der Aalst and M. Pesic. DecSerFlow: Towards a Truly Declarative Service Flow Language, pages 1--23. Springer, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. W. M. P. van der Aalst and M. Weske. Case handling: A new paradigm for business process support. Data Knowl. Eng., 53(2):129--162, May 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library

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            cover image ACM Conferences
            SAC '17: Proceedings of the Symposium on Applied Computing
            April 2017
            2004 pages
            ISBN:9781450344869
            DOI:10.1145/3019612

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            Publication History

            • Published: 3 April 2017

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