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Online Process Monitoring Using Incremental State-Space Expansion: An Exact Algorithm

: Schuster, Daniel; Zelst, Sebastiaan van


Fahland, D.:
Business Process Management : 18th International Conference, BPM 2020 Seville, Spain, September 13–18, 2020. Proceedings
Cham: Springer, 2020 (Lecture Notes in Computer Science 12168)
ISBN: 978-3-030-58665-2
ISBN: 978-3-030-58666-9
International Conference on Business Process Management (BPM) <18, 2020, Online>
Conference Paper
Fraunhofer FIT ()

The execution of (business) processes generates valuable tra-ces of event data in the information systems employed within companies. Recently, approaches for monitoring the correctness of the execution of running processes have been developed in the area of process mining, i.e., online conformance checking. The advantages of monitoring a process’ conformity during its execution are clear, i.e., deviations are detected as soon as they occur and countermeasures can immediately be initiated to reduce the possible negative effects caused by process deviations. Existing work in online conformance checking only allows for obtaining approximations of non-conformity, e.g., overestimating the actual severity of the deviation. In this paper, we present an exact, parameter-free, online conformance checking algorithm that computes conformance checking results on the fly. Our algorithm exploits the fact that the conformance checking problem can be reduced to a shortest path problem, by incrementally expanding the search space and reusing previously computed intermediate results. Our experiments show that our algorithm is able to outperform comparable state-of-the-art approximation algorithms.