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arXiv · 2305.05418

Measuring Rule-based LTLf Process Specifications: A Probabilistic Data-driven Approach

Alessio Cecconi·Luca Barbaro·Claudio Di Ciccio·Arik Senderovich
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Abstract

Declarative process specifications define the behavior of processes by means of rules based on Linear Temporal Logic on Finite Traces (LTLf). In a mining context, these specifications are inferred from, and checked on, multi-sets of runs recorded by information systems (namely, event logs). To this end, being able to gauge the degree to which process data comply with a specification is key. However, existing mining and verification techniques analyze the rules in isolation, thereby disregarding their interplay. In this paper, we introduce a framework to devise probabilistic measures for declarative process specifications. Thereupon, we propose a technique that measures the degree of satisfaction of specifications over event logs. To assess our approach, we conduct an evaluation with real-world data, evidencing its applicability in discovery, checking, and drift detection contexts.

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Alessio Cecconi, Luca Barbaro, Claudio Di Ciccio, Arik Senderovich. 2023-12-20. Measuring Rule-based LTLf Process Specifications: A Probabilistic Data-driven Approach. https://doi.org/10.1016/j.is.2023.102312

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