Workshop on Enterprise and Organizational Modeling and Simulation

Enterprise and Organizational Modeling and Simulation pp 20-36 | Cite as

Generating Event Logs Through the Simulation of Declare Models

  • Claudio Di Ciccio
  • Mario Luca Bernardi
  • Marta Cimitile
  • Fabrizio Maria Maggi
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 231)

Abstract

In the process mining field, several techniques have been developed during the last years, for the discovery of declarative process models from event logs. This type of models describes processes on the basis of temporal constraints. Every behavior that does not violate such constraints is allowed, and such characteristic has proven to be suitable for representing highly flexible processes. One way to test a process discovery technique is to generate an event log by simulating a process model, and then verify that the process discovered from such a log matches the original one. For this reason, a tool for generating event logs starting from declarative process models becomes vital for the evaluation of declarative process discovery techniques. In this paper, we present an approach for the automated generation of event logs, starting from process models that are based on Declare, one of the most used declarative modeling languages in the process mining literature. Our framework bases upon the translation of Declare constraints into regular expressions and on the utilization of Finite State Automata for the simulation. An evaluation of the implemented tool is presented, showing its effectiveness in both the generation of new logs and the replication of the behavior of existing ones. The presented evaluation also shows the capability of the tool of generating very large logs in a reasonably small amount of time, and its integration with state-of-the-art Declare modeling and discovery tools.

Keywords

Declare Regular expressions Declarative process models Process simulation Log generation 

Notes

Acknowledgments

The work of Claudio Di Ciccio has received funding from the EU Seventh Framework Programme (FP7/2007-2013) under grant agreement 318275 (GET Service).

References

  1. 1.
    Verbeek, H.M.W., Buijs, J.C.A.M., van Dongen, B.F., van der Aalst, W.M.P.: XES, XESame, and ProM 6. In: Soffer, P., Proper, E. (eds.) CAiSE Forum 2010. LNBIP, vol. 72, pp. 60–75. Springer, Heidelberg (2011) CrossRefGoogle Scholar
  2. 2.
    Scheer, A.-W., Nüttgens, M.: ARIS Architecture and reference models for business process management. In: van der Aalst, W.M.P., Desel, J., Oberweis, A. (eds.) Business Process Management. LNCS, vol. 1806, p. 376. Springer, Heidelberg (2000) CrossRefGoogle Scholar
  3. 3.
    Scheer, A.: ARIS toolset: a software product is born. Inf. Syst. 19(8), 607–624 (1994)CrossRefGoogle Scholar
  4. 4.
    van Dongen, B.: BPI challenge 2011 (2011)Google Scholar
  5. 5.
    van Dongen, B.: BPI challenge 2012 (2012)Google Scholar
  6. 6.
    Burattin, A., Sperduti, A.: PLG: a framework for the generation of business process models and their execution logs. In: Muehlen, M., Su, J. (eds.) BPM 2010 Workshops. LNBIP, vol. 66, pp. 214–219. Springer, Heidelberg (2011) CrossRefGoogle Scholar
  7. 7.
    Jensen, K., Kristensen, L.M., Wells, L.: Coloured petri nets and cpn tools for modelling and validation of concurrent systems. Int. J. Softw. Tools Technol. Transf. 9(3), 213–254 (2007)CrossRefGoogle Scholar
  8. 8.
    Hee, K.V., Liu, Z.: Generating benchmarks by random stepwise refinement of petri nets. In: Donatelli, S., Kleijn, J., Machado, R., Fernandes, J. (eds.) PETRI NETS 2010, pp. 403–417. CEUR-ws.org (2012)Google Scholar
  9. 9.
    Bergmann, G., Horváth, A., Ráth, I., Varró, D.: A benchmark evaluation of incremental pattern matching in graph transformation. In: Ehrig, H., Heckel, R., Rozenberg, G., Taentzer, G. (eds.) ICGT 2008. LNCS, vol. 5214, pp. 396–410. Springer, Heidelberg (2008) CrossRefGoogle Scholar
  10. 10.
    Pesic, M., van der Aalst, W.M.P.: A declarative approach for flexible business processes management. In: Eder, J., Dustdar, S. (eds.) BPM Workshops 2006. LNCS, vol. 4103, pp. 169–180. Springer, Heidelberg (2006) CrossRefGoogle Scholar
  11. 11.
    Fahland, D., Lübke, D., Mendling, J., Reijers, H., Weber, B., Weidlich, M., Zugal, S.: Declarative versus imperative process modeling languages: the issue of understandability. In: Halpin, T., Krogstie, J., Nurcan, S., Proper, E., Schmidt, R., Soffer, P., Ukor, R. (eds.) Enterprise, Business-Process and Information Systems Modeling. LNBIP, vol. 29, pp. 353–366. Springer, Heidelberg (2009) CrossRefGoogle Scholar
  12. 12.
    Pichler, P., Weber, B., Zugal, S., Pinggera, J., Mendling, J., Reijers, H.A.: Imperative versus declarative process modeling languages: an empirical investigation. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) BPM Workshops 2011, Part I. LNBIP, vol. 99, pp. 383–394. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  13. 13.
    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
  14. 14.
    Maggi, F.M.: Declarative process mining with the Declare component of ProM. In: BPM (Demos) (2013)Google Scholar
  15. 15.
    Maggi, F.M., Bose, R.P.J.C., van der Aalst, W.M.P.: Efficient discovery of understandable declarative process models from event logs. In: Ralyté, J., Franch, X., Brinkkemper, S., Wrycza, S. (eds.) CAiSE 2012. LNCS, vol. 7328, pp. 270–285. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  16. 16.
    Bernardi, M.L., Cimitile, M., Di Francescomarino, C., Maggi, F.M.: Using discriminative rule mining to discover declarative process models with non-atomic activities. In: Bikakis, A., Fodor, P., Roman, D. (eds.) RuleML 2014. LNCS, vol. 8620, pp. 281–295. Springer, Heidelberg (2014) Google Scholar
  17. 17.
    Pesic, M., Schonenberg, H., van der Aalst, W.M.P.: DECLARE: full support for loosely-structured processes. In: EDOC, pp. 287–300 (2007)Google Scholar
  18. 18.
    van der Aalst, W.M.P.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer, New York (2011) CrossRefMATHGoogle Scholar
  19. 19.
    Dumas, M., La Rosa, M., Mendling, J., Reijers, H.A.: Fundamentals of Business Process Management. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  20. 20.
    van der Aalst, W.M.P.: The application of petri nets to workflow management. J. Circ. Syst. Comput. 8(1), 21–66 (1998)CrossRefGoogle Scholar
  21. 21.
    van der Aalst, W.M.P.: Verification of workflow nets. In: Azéma, P., Balbo, G. (eds.) ICATPN 1997. LNCS, vol. 1248, pp. 407–426. Springer, Heidelberg (1997) CrossRefGoogle Scholar
  22. 22.
    van der Aalst, W.M.P., ter Hofstede, A.H.M.: YAWL: yet another workflow language. Inf. Syst. 30(4), 245–275 (2005)CrossRefGoogle Scholar
  23. 23.
    Di Ciccio, C., Mecella, M., Scannapieco, M., Zardetto, D., Catarci, T.: MailOfMine – analyzing mail messages for mining artful collaborative processes. In: Aberer, K., Damiani, E., Dillon, T. (eds.) SIMPDA 2011. LNBIP, vol. 116, pp. 55–81. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  24. 24.
    van der Aalst, W., Pesic, M., Schonenberg, H.: Declarative workflows: balancing between flexibility and support. Computer Science - R&D 23, 99–113 (2009)Google Scholar
  25. 25.
    De Giacomo, G., Vardi, M.Y.: Linear temporal logic and linear dynamic logic on finite traces. In: IJCAI (2013)Google Scholar
  26. 26.
    De Giacomo, G., De Masellis, R., Montali, M.: Reasoning on ltl on finite traces: Insensitivity to infiniteness. In: AAAI (2014)Google Scholar
  27. 27.
    Alberti, M., Chesani, F., Gavanelli, M., Lamma, E., Mello, P., Torroni, P.: Verifiable agent interaction in abductive logic programming: the sciff framework. ACM Trans. Comput. Log. 9(4), 29:1–29:43 (2008)CrossRefGoogle Scholar
  28. 28.
    Chesani, F., Lamma, E., Mello, P., Montali, M., Riguzzi, F., Storari, S.: Exploiting inductive logic programming techniques for declarative process mining. In: Jensen, K., van der Aalst, W.M.P. (eds.) Transactions on Petri Nets and Other Models of Concurrency II. LNCS, vol. 5460, pp. 278–295. Springer, Heidelberg (2009) CrossRefGoogle Scholar
  29. 29.
    Gisburg, S., Rose, G.F.: Preservation of languages by transducers. Inf. Control 9(2), 153–176 (1966)MathSciNetCrossRefMATHGoogle Scholar
  30. 30.
    Prescher, J., Di Ciccio, C., Mendling, J.: From declarative processes to imperative models. In: SIMPDA, pp. 162–173, CEUR-WS.org (2014)Google Scholar
  31. 31.
    van Dongen, B.: BPI challenge 2014 (2014)Google Scholar
  32. 32.
    Di Ciccio, C., Mecella, M.: A two-step fast algorithm for the automated discovery of declarative workflows. In: CIDM, IEEE, pp. 135–142 (2013)Google Scholar
  33. 33.
    de Medeiros, A.A., Günther, C.W.: Process mining: Using CPN tools to create test logs for mining algorithms. In: Proceedings of the sixth workshop on the practical use of coloured Petri nets and CPN tools (CPN 2005), vol. 576 (2005)Google Scholar
  34. 34.
    Di Ciccio, C., Marrella, A., Russo, A.: Knowledge-intensive Processes: Characteristics, requirements and analysis of contemporary approaches. J. Data Semant. 4(1), 29–57 (2015)CrossRefGoogle Scholar
  35. 35.
    van der Aalst, W.M.P., Pesic, M.: DecSerFlow: towards a truly declarative service flow language. In: Bravetti, M., Núñez, M., Zavattaro, G. (eds.) WS-FM 2006. LNCS, vol. 4184, pp. 1–23. Springer, Heidelberg (2006) CrossRefGoogle Scholar
  36. 36.
    van der Aalst, W.M.P., Pesic, M., Schonenberg, H.: Declarative workflows: Balancing between flexibility and support. Comput. Sci. R&D 23(2), 99–113 (2009)Google Scholar
  37. 37.
    Schunselaar, D.M.M., Maggi, F.M., Sidorova, N., van der Aalst, W.M.P.: Configurable declare: designing customisable flexible process models. In: Meersman, R., et al. (eds.) OTM 2012, Part I. LNCS, vol. 7565, pp. 20–37. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  38. 38.
    Westergaard, M., Slaats, T.: Cpn tools 4: A process modeling tool combining declarative and imperative paradigms. In: BPM (Demos) (2013)Google Scholar
  39. 39.
    Di Ciccio, C., Maggi, F.M., Mendling, J.: Discovering target-branched declare constraints. In: Sadiq, S., Soffer, P., Völzer, H. (eds.) BPM 2014. LNCS, vol. 8659, pp. 34–50. Springer, Heidelberg (2014) Google Scholar
  40. 40.
    Di Ciccio, C., Mecella, M., Mendling, J.: The effect of noise on mined declarative constraints. In: Ceravolo, P., Accorsi, R., Cudre-Mauroux, P. (eds.) SIMPDA 2013. LNBIP, vol. 203, pp. 1–24. Springer, Heidelberg (2015) Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Claudio Di Ciccio
    • 1
  • Mario Luca Bernardi
    • 2
  • Marta Cimitile
    • 3
  • Fabrizio Maria Maggi
    • 4
  1. 1.Vienna University of Economics and BusinessViennaAustria
  2. 2.University of SannioBeneventoItaly
  3. 3.Unitelma Sapienza UniversityRomeItaly
  4. 4.University of TartuTartuEstonia

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