Verification of Data Aware Business Process Models: A Methodological Survey of Research Results and Challenges

  • Raffaele Dell’AversanaEmail author
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 373)


Business Process Management is a discipline that gives a systematic approach to the development of more efficient and effective organizations, enabling quick adaptation to the changes of the business environment. For this reason modeling languages such as BPMN [1] have a wide adoption in modern organizations. Such modeling languages are used for the design and reengineering of Business Processes and have the advantage of having a representation that is not only easy to understand by all the stakeholders but also machine processable.

However any executable model of a business process could contain potential problems (just like any computer software), so there are several research branches focused on formal verification of the models. The verification is not limited to check the correctness of the model but also to verify properties of the model, such as conformance to business rules.

This short paper presents a survey of recent approaches to verification of data-aware business process models and identifies a range of open research challenges.


business process re-engineering business process modeling formal verification static verification logic programming 


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  1. 1.
    OMG: Business Process Model and Notation (BPMN), Version 2.0 (January 2011)Google Scholar
  2. 2.
    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
  3. 3.
    van der Aalst, W.M.P., ter Hofstede, A.H.M.: Yawl: Yet another workflow language. Inf. Syst. 30(4), 245–275 (2005)Google Scholar
  4. 4.
    van der Aalst, W.M.P.: The application of petri nets to workflow management. Journal of Circuits, Systems, and Computers 8(1), 21–66 (1998)CrossRefGoogle Scholar
  5. 5.
    Nigam, A., Caswell, N.S.: Business artifacts: An approach to operational specification. IBM Syst. J. 42(3), 428–445 (2003)Google Scholar
  6. 6.
    Hull, R.: Artifact-centric business process models: Brief survey of research results and challenges. In: Meersman, R., Tari, Z. (eds.) OTM 2008, Part II. LNCS, vol. 5332, pp. 1152–1163. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  7. 7.
    Deutsch, A., Hull, R., Patrizi, F., Vianu, V.: Automatic verification of data-centric business processes. In: Proceedings of the 12th International Conference on Database Theory, ICDT 2009, pp. 252–267. ACM, New York (2009)Google Scholar
  8. 8.
    Damaggio, E., Deutsch, A., Vianu, V.: Artifact systems with data dependencies and arithmetic. ACM Trans. Database Syst. 37(3), 22 (2012)Google Scholar
  9. 9.
    Calvanese, D., De Giacomo, G., Montali, M.: Foundations of data-aware process analysis: A database theory perspective. In: Proceedings of the 32nd Symposium on Principles of Database Systems, PODS 2013, pp. 1–12. ACM, New York (2013)CrossRefGoogle Scholar
  10. 10.
    Bagheri Hariri, B., Calvanese, D., De Giacomo, G., Deutsch, A., Montali, M.: Verification of relational data-centric dynamic systems with external services. In: Proceedings of the 32nd Symposium on Principles of Database Systems, PODS 2013, pp. 163–174. ACM, New York (2013)CrossRefGoogle Scholar
  11. 11.
    Giordano, L., Martelli, A., Spiotta, M., Dupré, D.T.: Business process verification with constraint temporal answer set programming. TPLP 13(4-5), 641–655 (2013)zbMATHGoogle Scholar
  12. 12.
    Gelfond, M.: Answer sets. In: van Harmelen, F., van Harmelen, F., Lifschitz, V., Porter, B. (eds.) Handbook of Knowledge Representation. Elsevier Science, San Diego (2007)Google Scholar
  13. 13.
    Montali, M., Chesani, F., Mello, P., Maggi, F.M.: Towards data-aware constraints in declare. In: Proceedings of the 28th Annual ACM Symposium on Applied Computing, SAC 2013, pp. 1391–1396. ACM, New York (2013)CrossRefGoogle Scholar
  14. 14.
    Proietti, M., Smith, F.: Reasoning on data-aware business processes with constraint logic. In: Proceedings of the 4th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2014). CEUR-WS, vol. 1293 (2014)Google Scholar
  15. 15.
    Jaffar, J., Maher, M.J.: Constraint logic programming: A survey. Journal of Logic Programming 19, 503–581 (1994)MathSciNetGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.School of Advanced Studies G. D’AnnunzioUniversity of Chieti-PescaraChietiItaly

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