Abstract
Conformance checking is a key process mining task for comparing the expected behavior captured in a process model and the actual behavior recorded in a log. While this problem has been extensively studied for pure control-flow processes, conformance checking with multi-perspective processes is still at its infancy. In this paper, we attack this challenging problem by considering processes that combine the data and control-flow dimensions. In particular, we adopt data Petri nets (DPNs) as the underlying reference formalism, and show how solid, well-established automated reasoning techniques can be effectively employed for computing conformance metrics and data-aware alignments. We do so by introducing the CoCoMoT (Computing Conformance Modulo Theories) framework, with a fourfold contribution. First, we show how SAT-based encodings studied in the pure control-flow setting can be lifted to our data-aware case, using SMT as the underlying formal and algorithmic framework. Second, we introduce a novel preprocessing technique based on a notion of property-preserving clustering, to speed up the computation of conformance checking outputs. Third, we provide a proof-of-concept implementation that uses a state-of-the-art SMT solver and report on preliminary experiments. Finally, we discuss how CoCoMoT directly lends itself to a number of further tasks, like multi- and anti-alignments, log analysis by clustering, and model repair.
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Notes
- 1.
In contrast to [22], we do not distinguish between synchronous moves with correct and incorrect write operations, and defer this differentiation to the cost function.
- 2.
Notice that in this paper we do not fix the exact algorithm for trace clustering, which in our implementation is achieved by exhaustively comparing log traces.
- 3.
Instead of the sum, also other aggregation functions can be used, e.g., maximum.
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This research has been partially supported by the UNIBZ projects SMART-APP, REKAP, VERBA and DUB.
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Felli, P., Gianola, A., Montali, M., Rivkin, A., Winkler, S. (2021). CoCoMoT: Conformance Checking of Multi-perspective Processes via SMT. In: Polyvyanyy, A., Wynn, M.T., Van Looy, A., Reichert, M. (eds) Business Process Management. BPM 2021. Lecture Notes in Computer Science(), vol 12875. Springer, Cham. https://doi.org/10.1007/978-3-030-85469-0_15
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