Soundness of data-aware, case-centric processes

Abstract

In recent years, a plethora of foundational results and corresponding techniques and tools has been developed to support the modeling, analysis, execution and improvement of business processes along their entire lifecycle. A major shortcoming of the analysis techniques is that they solely focus on the control-flow dimension of the process, omitting how business objects (i.e., cases) and their data affect and are manipulated by process instances and their tasks. In this work, we aim at filling this gap. We recast the classical notion of case-centric business process in a data-aware context. An emitter action is used to generate new cases, and while a case flows through the process control-flow, corresponding data are created, updated, and deleted by operating over a full-fledged relational database with constraints. To make our investigation concrete, we ground it on the recently introduced framework of data-centric dynamic systems (DCDSs). We reformulate the standard correctness criterion of soundness into this rich setting, and show that it is in general undecidable to check. We then provide a fine-grained analysis on the role of data in business processes. We substantiate this analysis by introducing a class of case-centric DCDSs that enjoys good modeling principles, and at the same time guarantees decidability of soundness. Decidability is obtained by finding a cutoff on the number of process instances that must be subject to the soundness test. We finally show that the introduced modeling guidelines are strict, in the sense that weakening even one single requirement they pose leads to undecidability.

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Notes

  1. 1.

    Intuitively, state-boundedness requires that the number of data values stored in each single state of the system is bounded. Unboundedly many values can still be encountered within and across the runs of the system.

  2. 2.

    Thanks to set semantics, there is no need to explicitly encode that the only column of \({ Group } \) is its primary key, and similarly for the combination of the only two columns of \({ Trusts } \).

  3. 3.

    Considering in particular those with equality symmetry.

  4. 4.

    Recall that each case initially starts from the \({\mathtt {in}} \) state, in accordance with the specification of \({\textsc {new}}\hbox {-}{\textsc {case}}\).

  5. 5.

    \({ C } ({\textsf {c}})\) is added just for compatibility with the definition, but it is ensured by construction, since parameter \({\textsf {c}} \) points to \({ C } \).

  6. 6.

    Recall that \({ Leader } \) can be freely queried, being cardinality-immutable.

  7. 7.

    We ignore the contribution of the countably infinite data domain.

  8. 8.

    Read-only and cardinality-immutable relations constitute an exception to this.

  9. 9.

    http://sourceforge.net/projects/bizartifact/.

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Acknowledgments

The authors are partially supported by the EU project Optique (FP7-IP-318338), and by the UNIBZ internal projects KENDO and OnProm.

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Correspondence to Marco Montali.

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Montali, M., Calvanese, D. Soundness of data-aware, case-centric processes. Int J Softw Tools Technol Transfer 18, 535–558 (2016). https://doi.org/10.1007/s10009-016-0417-2

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Keywords

  • Processor-centric Case
  • Data-centric Dynamic Systems (DCDS)
  • Full-fledged Relational Database
  • Foreign Key
  • Combat Level