Add Data into Business Process Verification: Bridging the Gap between Theory and Practice

Authors

  • Riccardo De Masellis Fondazione Bruno Kessler
  • Chiara Di Francescomarino Fondazione Bruno Kessler
  • Chiara Ghidini Fondazione Bruno Kessler
  • Marco Montali Free University of Bozen-Bolzano
  • Sergio Tessaris Free University of Bozen-Bolzano

DOI:

https://doi.org/10.1609/aaai.v31i1.10688

Keywords:

data-aware business process modeling, workflow nets, relational databases, formal verification, planning

Abstract

The need to extend business process languages with the capability to model complex data objects along with the control flow perspective has lead to significant practical and theoretical advances in the field of Business Process Modeling (BPM).On the practical side, there are several suites for control flow and data modeling; nonetheless, when it comes to formal verification, the data perspective is abstracted away due to the intrinsic difficulty of handling unbounded data. On the theoretical side, there is significant literature providing decidability results for expressive data-aware processes. However, they struggle to produce a concrete impact as being far from real BPM architectures and, most of all, not providing actual verification tools. In this paper we aim at bridging such a gap: we provide a concrete framework which, on the one hand, being based on Petri Nets and relational models, is close to the widely used BPM suites, and on the other is grounded on solid formal basis which allow to perform formal verification tasks. Moreover, we show how to encode our framework in an action language so as to perform reachability analysis using virtually any state-of-the-art planner.

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Published

2017-02-12

How to Cite

De Masellis, R., Di Francescomarino, C., Ghidini, C., Montali, M., & Tessaris, S. (2017). Add Data into Business Process Verification: Bridging the Gap between Theory and Practice. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/10.1609/aaai.v31i1.10688

Issue

Section

AAAI Technical Track: Knowledge Representation and Reasoning