Model Checking of Mixed-Paradigm Process Models in a Discovery Context

Finding the Fit Between Declarative and Procedural
  • Johannes De Smedt
  • Claudio Di Ciccio
  • Jan Vanthienen
  • Jan Mendling
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 281)

Abstract

The act of retrieving process models from event-based data logs can offer valuable information to business owners. Many approaches have been proposed for this purpose, mining for either a procedural or declarative outcome. A blended approach that combines both process model paradigms exists and offers a great way to deal with process environments which consist of different layers of flexibility. In this paper, it will be shown how to check such models for correctness, and how this checking can contribute to retrieving the models as well. The approach is based on intersecting both parts of the model and provides an effective way to check (i) whether the behavior is aligned, and (ii) where the model can be improved according to errors that arise along the respective paradigms. To this end, we extend the functionality of Fusion Miner, a mixed-paradigm process miner, in a way to inspect which amount of flexibility is right for the event log. The procedure is demonstrated with an implemented model checker and verified on real-life event logs.

Keywords

Declarative process models Model checking Process mining 

References

  1. 1.
    van der Aalst, W.M.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer, New York (2011)CrossRefMATHGoogle Scholar
  2. 2.
    Weijters, A., van der Aalst, W.M., De Medeiros, A.A.: Process mining with the heuristics miner-algorithm. TU Eindhoven, Technical report WP 166 (2006)Google Scholar
  3. 3.
    van der Aalst, W.M., Weijters, T., Maruster, L.: Workflow mining: discovering process models from event logs. IEEE Trans. Knowl. Data Eng. 16(9), 1128–1142 (2004)CrossRefGoogle Scholar
  4. 4.
    Werf, J.M.E.M., Dongen, B.F., Hurkens, C.A.J., Serebrenik, A.: Process discovery using integer linear programming. In: Hee, K.M., Valk, R. (eds.) PETRI NETS 2008. LNCS, vol. 5062, pp. 368–387. Springer, Heidelberg (2008). doi:10.1007/978-3-540-68746-7_24 CrossRefGoogle Scholar
  5. 5.
    Maggi, F.M., Mooij, A.J., van der Aalst, W.M.: User-guided discovery of declarative process models. In: CIDM, pp. 192–199. IEEE (2011)Google Scholar
  6. 6.
    Di Ciccio, C., Mecella, M.: A two-step fast algorithm for the automated discovery of declarative workflows. In: CIDM, pp. 135–142. IEEE (2013)Google Scholar
  7. 7.
    Murata, T.: Petri nets: properties, analysis and applications. Proc. IEEE 77(4), 541–580 (1989)CrossRefGoogle Scholar
  8. 8.
    Pesic, M., Schonenberg, H., van der Aalst, W.M.: Declare: full support for loosely-structured processes. In: EDOC, p. 287. IEEE(2007)Google Scholar
  9. 9.
    Maggi, F.M., Slaats, T., Reijers, H.A.: The automated discovery of hybrid processes. In: Sadiq, S., Soffer, P., Völzer, H. (eds.) BPM 2014. LNCS, vol. 8659, pp. 392–399. Springer, Cham (2014). doi:10.1007/978-3-319-10172-9_27 Google Scholar
  10. 10.
    Smedt, J., Weerdt, J., Vanthienen, J.: Multi-paradigm process mining: retrieving better models by combining rules and sequences. In: Meersman, R., Panetto, H., Dillon, T., Missikoff, M., Liu, L., Pastor, O., Cuzzocrea, A., Sellis, T. (eds.) OTM 2014. LNCS, vol. 8841, pp. 446–453. Springer, Heidelberg (2014). doi:10.1007/978-3-662-45563-0_26 Google Scholar
  11. 11.
    De Smedt, J., De Weerdt, J., Vanthienen, J.: Fusion miner: process discovery for mixed-paradigm models. Decis. Support Syst. 77, 123–136 (2015)CrossRefGoogle Scholar
  12. 12.
    Westergaard, M.: CPN tools 4: multi-formalism and extensibility. In: Colom, J.-M., Desel, J. (eds.) PETRI NETS 2013. LNCS, vol. 7927, pp. 400–409. Springer, Heidelberg (2013). doi:10.1007/978-3-642-38697-8_22 CrossRefGoogle Scholar
  13. 13.
    Pesic, M., Aalst, W.M.P.: A declarative approach for flexible business processes management. In: Eder, J., Dustdar, S. (eds.) BPM 2006. LNCS, vol. 4103, pp. 169–180. Springer, Heidelberg (2006). doi:10.1007/11837862_18 CrossRefGoogle Scholar
  14. 14.
    De Smedt, J., De Weerdt, J., Vanthienen, J., Poels, G.: Mixed-paradigm process modeling with intertwined state spaces. Bus. Inf. Syst. Eng. 58, 19–29 (2016)CrossRefGoogle Scholar
  15. 15.
    Westergaard, M., Slaats, T.: Mixing paradigms for more comprehensible models. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 283–290. Springer, Heidelberg (2013). doi:10.1007/978-3-642-40176-3_24 CrossRefGoogle Scholar
  16. 16.
    Di Ciccio, C., Maggi, F.M., Montali, M., Mendling, J.: Ensuring model consistency in declarative process discovery. In: Motahari-Nezhad, H.R., Recker, J., Weidlich, M. (eds.) BPM 2015. LNCS, vol. 9253, pp. 144–159. Springer, Cham (2015). doi:10.1007/978-3-319-23063-4_9 CrossRefGoogle Scholar
  17. 17.
    Prescher, J., Di Ciccio, C., Mendling, J.: From declarative processes to imperative models. In: SIMPDA, pp. 162–173 (2014)Google Scholar
  18. 18.
    Di Ciccio, C., Mecella, M.: On the discovery of declarative control flows for artful processes. ACM Trans. Manage. Inf. Syst. 5(4), 24:1–24:37 (2015)CrossRefGoogle Scholar
  19. 19.
    Westergaard, M., Stahl, C., Reijers, H.A.: Unconstrainedminer: efficient discovery of generalized declarative process models. Technical report, BPMcenter (2013)Google Scholar
  20. 20.
    Desel, J., Reisig, W.: Place/transition petri nets. In: Reisig, W., Rozenberg, G. (eds.) ACPN 1996. LNCS, vol. 1491, pp. 122–173. Springer, Heidelberg (1998). doi:10.1007/3-540-65306-6_15 CrossRefGoogle Scholar
  21. 21.
    Smedt, J., Weerdt, J., Serral, E., Vanthienen, J.: Improving understandability of declarative process models by revealing hidden dependencies. In: Nurcan, S., Soffer, P., Bajec, M., Eder, J. (eds.) CAiSE 2016. LNCS, vol. 9694, pp. 83–98. Springer, Cham (2016). doi:10.1007/978-3-319-39696-5_6 Google Scholar
  22. 22.
    Adriansyah, A., Buijs, J.C.A.M.: Mining process performance from event logs. In: Rosa, M., Soffer, P. (eds.) BPM 2012. LNBIP, vol. 132, pp. 217–218. Springer, Heidelberg (2013). doi:10.1007/978-3-642-36285-9_23 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Johannes De Smedt
    • 1
  • Claudio Di Ciccio
    • 2
  • Jan Vanthienen
    • 1
  • Jan Mendling
    • 2
  1. 1.Department of Decision Sciences and Information Management, Faculty of Economics and BusinessKU LeuvenLeuvenBelgium
  2. 2.Department of Information Systems and OperationsVienna University of Economics and BusinessViennaAustria

Personalised recommendations