Abstract
Process managers apply conformance checking techniques to identify deviations between the desired and the actual execution of a process. From a process-level perspective, these deviations often involve multiple interrelated events, for example if activities are executed in the wrong order or are unnecessarily repeated. However, state-of-the-art conformance checking techniques do not reveal these process-level deviations, instead identifying only event-level deviations in the form of inserted or skipped events. To address this shortcoming, this paper presents an approach that discovers process-level deviations from event-level insights provided by alignment-based conformance checking techniques. These deviations are discovered as instantiations of five commonly used patterns of non-conformance: inserted, skipped, repeated, replaced, and swapped. The approach is designed to choose patterns according to a user’s preferences and contextualize them within parallelism and choices in the process model. Our evaluation shows that it reliably detects process-level deviations, thus providing process managers with more comprehensive information on process conformance.
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Notes
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Note that in this paper, any alignment visualization places the trace above the model sequence.
- 2.
Note that the original source [15] also proposes a loop pattern, but in the context of alignments, this is simply a specific version of the repeated pattern.
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Grohs, M., van der Aa, H., Rehse, JR. (2024). Beyond Log and Model Moves in Conformance Checking: Discovering Process-Level Deviation Patterns. In: Marrella, A., Resinas, M., Jans, M., Rosemann, M. (eds) Business Process Management. BPM 2024. Lecture Notes in Computer Science, vol 14940. Springer, Cham. https://doi.org/10.1007/978-3-031-70396-6_22
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