Abstract
Given a process model representing the expected behavior of a business process and an event log recording its actual execution, the problem of business process conformance checking is that of detecting and describing the differences between the process model and the log. A desirable feature is to produce a minimal yet complete set of behavioral differences. Existing conformance checking techniques that achieve these properties do not scale up to real-life process models and logs. This paper presents an approach that addresses this shortcoming by exploiting automata-based techniques. A log is converted into a deterministic automaton in a lossless manner, the input process model is converted into another minimal automaton, and a minimal error-correcting synchronized product of both automata is calculated using an A* heuristic. The resulting automaton is used to extract alignments between traces of the model and traces of the log, or statements describing behavior observed in the log but not captured in the model. An evaluation on synthetic and real-life models and logs shows that the proposed approach outperforms a state-of-the-art method for complete conformance checking.
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Notes
- 1.
\( MultiSet \) retrieves the multiset representing the labels in a trace or the labels of a set of arcs.
- 2.
In case of \(( match , B)\) we have a current cost of zero since it is a match (i.e. \( g ( n ) = 0\)), and a future cost of one (i.e. \( h ( n , c) = \left| \{D^1,E^1\} \setminus \{C^1,D^1,E^1\}\right| + \left| \{C^1,D^1,E^1\} \setminus \{D^1,E^1\}\right| = 1\)).
- 3.
In case of \(( rhide , B)\) we have a current cost of one since it is a hide (i.e. \( g ( n ) = 1\)), and a future cost of two (i.e. \( h ( n , c) = \left| \{B^1,D^1,E^1\} \setminus \{C^1,D^1,E^1\}\right| + \left| \{C^1,D^1,E^1\} \setminus \{B^1,D^1,E^1\}\right| = 2\)).
- 4.
Available from http://apromore.org/tools.
- 5.
“A* Cost-based Fitness Express with ILP, assuming at most 32,767 tokens in each place”.
- 6.
Strictly speaking, trace alignment requires easy-soundness while our approach requires safeness. However both requirements are satisfied by soundness.
- 7.
An alignment was filtered if it had a higher cost than that computed by one-optimal alignment or if it represented the swap of the label of an invisible task with that of a visible one.
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This research is partly funded by the Australian Research Council (grant DP150103356) and the Estonian Research Council (grant IUT20-55).
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Reißner, D., Conforti, R., Dumas, M., La Rosa, M., Armas-Cervantes, A. (2017). Scalable Conformance Checking of Business Processes. In: Panetto, H., et al. On the Move to Meaningful Internet Systems. OTM 2017 Conferences. OTM 2017. Lecture Notes in Computer Science(), vol 10573. Springer, Cham. https://doi.org/10.1007/978-3-319-69462-7_38
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