Abstract
Token-based replay used to be the standard way to conduct conformance checking. With the uptake of more advanced techniques (e.g., alignment based), token-based replay got abandoned. However, despite decomposition approaches and heuristics to speed-up computation, the more advanced conformance checking techniques have limited scalability, especially when traces get longer and process models more complex. This paper presents an improved token-based replay approach that is much faster and scalable. Moreover, the approach provides more accurate diagnostics that avoid known problems (e.g., “token flooding”) and help to pinpoint compliance problems. The novel token-based replay technique has been implemented in the PM4Py process mining library. We will show that the replay technique outperforms state-of-the-art techniques in terms of speed and/or diagnostics.
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Notes
- 1.
With a process discovery technique, a process model is constructed capturing the behavior seen in an event log. See the book [4] for an introduction to the most popular process discovery algorithms.
- 2.
A marking \(M \in \mathcal {B}(P)\) is a place multiset. We denote with \(\mathcal {U}_M\) the universe of markings.
- 3.
During the activation of the sequence, some places could still have missing tokens.
- 4.
The logs are available at the URL https://data.4tu.nl/repository/collection:event_logs.
- 5.
- 6.
References
van der Aalst, W.M.P.: Structural characterizations of sound workflow nets. Comput. Sci. Rep. 96(23), 18–22 (1996)
van der Aalst, W.M.P.: Decomposing process mining problems using passages. In: Haddad, S., Pomello, L. (eds.) PETRI NETS 2012. LNCS, vol. 7347, pp. 72–91. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31131-4_5
van der Aalst, W.M.P.: Distributed process discovery and conformance checking. In: de Lara, J., Zisman, A. (eds.) FASE 2012. LNCS, vol. 7212, pp. 1–25. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28872-2_1
van der Aalst, W.M.P.: Data science in action. Process Mining, pp. 3–23. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-49851-4_1
van der Aalst, W.M.P., Adriansyah, A., van Dongen, B.: Replaying history on process models for conformance checking and performance analysis. Wiley Interdisc. Rev. Data Min. Knowl. Discov. 2(2), 182–192 (2012)
Adriansyah, A.: Aligning observed and modeled behavior. Ph.D. thesis, Department of Mathematics and Computer Science (2014)
Adriansyah, A., Sidorova, N., van Dongen, B.: Cost-based fitness in conformance checking. In: 2011 11th International Conference on Application of Concurrency to System Design (ACSD), pp. 57–66. IEEE (2011)
Bauer, M., van der Aa, H., Weidlich, M.: Estimating process conformance by trace sampling and result approximation. In: Hildebrandt, T., van Dongen, B.F., Röglinger, M., Mendling, J. (eds.) BPM 2019. LNCS, vol. 11675, pp. 179–197. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-26619-6_13
Berti, A., van der Aalst, W.M.P.: Reviving token-based replay: increasing speed while improving diagnostics. In: Algorithms & Theories for the Analysis of Event Data (ATAED 2019) (CEUR 2371), pp. 87–103 (2019)
vanden Broucke, S.K.L.M., Munoz-Gama, J., Carmona, J., Baesens, B., Vanthienen, J.: Event-based real-time decomposed conformance analysis. In: Meersman, R., et al. (eds.) OTM 2014. LNCS, vol. 8841, pp. 345–363. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-45563-0_20
Carmona, J., Dongen, B., Solti, A., Weidlich, M.: Conformance Checking: Relating Processes and Models. Springer, Heidelberg (2018). https://doi.org/10.1007/978-3-319-99414-7
de Leoni, M., van der Aalst, W.M.P., Dees, M.: A general framework for correlating business process characteristics. In: Sadiq, S., Soffer, P., Völzer, H. (eds.) BPM 2014. LNCS, vol. 8659, pp. 250–266. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-10172-9_16
Esparza, J.: Reduction and synthesis of live and bounded free choice petri nets. Inf. Comput. 114(1), 50–87 (1994)
Kerremans, M.: Gartner Market Guide for Process Mining, Research Note G00353970 (2018). www.gartner.com
Lee, W.L.J., Verbeek, H., Munoz-Gama, J., van der Aalst, W.M.P., Sepúlveda, M.: Recomposing conformance: closing the circle on decomposed alignment-based conformance checking in process mining. Inf. Sci. 466, 55–91 (2018)
Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Discovering block-structured process models from event logs - a constructive approach. In: Colom, J.-M., Desel, J. (eds.) PETRI NETS 2013. LNCS, vol. 7927, pp. 311–329. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38697-8_17
Leemans, S.J., Fahland, D., van der Aalst, W.M.P.: Scalable process discovery and conformance checking. Softw. Syst. Model. 17(2), 599–631 (2018)
Martínez, J.: A simple and fast algorithm to obtain all invariants of a generalised Petri net. In: Girault, C., Reisig, W. (eds.) Application and Theory of Petri nets. INFORMATIK, vol. 52, pp. 301–310. Springer, Heidelberg (1982). https://doi.org/10.1007/978-3-642-68353-4_47
de Medeiros, A.K.A., Weijters, A.J., van der Aalst, W.M.P.: Genetic process mining: an experimental evaluation. Data Min. Knowl. Disc. 14(2), 245–304 (2007)
Miyamoto, T., Kumagai, S.: Calculating place capacity for Petri nets using unfoldings. In: International Conference on Application of Concurrency to System Design (ACSD) 1998, pp. 143–151. IEEE (1998)
Molka, T., Redlich, D., Drobek, M., Caetano, A., Zeng, X.J., Gilani, W.: Conformance checking for BPMN-based process models. In: Proceedings of the 29th Annual ACM Symposium on Applied Computing, pp. 1406–1413 (2014)
Munoz-Gama, J., Carmona, J., van der Aalst, W.M.P.: Single-entry single-exit decomposed conformance checking. Inf. Syst. 46, 102–122 (2014)
Reißner, D., Armas-Cervantes, A., Conforti, R., Dumas, M., Fahland, D., La Rosa, M.: Scalable alignment of process models and event logs: an approach based on automata and s-components. arXiv preprint arXiv:1910.09767 (2019)
Reißner, D., Conforti, R., Dumas, M., La Rosa, M., Armas-Cervantes, A.: Scalable conformance checking of business processes. OTM 2017. LNCS, vol. 10573, pp. 607–627. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-69462-7_38
Rogge-Solti, A., Senderovich, A., Weidlich, M., Mendling, J., Gal, A.: In log and model we trust? A generalized conformance checking framework. In: La Rosa, M., Loos, P., Pastor, O. (eds.) BPM 2016. LNCS, vol. 9850, pp. 179–196. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45348-4_11
Rozinat, A., van der Aalst, W.M.P.: Conformance testing: measuring the fit and appropriateness of event logs and process models. In: Bussler, C.J., Haller, A. (eds.) BPM 2005. LNCS, vol. 3812, pp. 163–176. Springer, Heidelberg (2006). https://doi.org/10.1007/11678564_15
Rozinat, A., van der Aalst, W.M.P.: Conformance checking of processes based on monitoring real behavior. Inf. Syst. 33(1), 64–95 (2008)
Shugurov, I., Mitsyuk, A.: Applying MapReduce to conformance checking. Proc. Inst. Syst. Program. RAS 28, 103–122 (2016). https://doi.org/10.15514/ISPRAS-2016-28(3)-7
Taymouri, F., Carmona, J.: An evolutionary technique to approximate multiple optimal alignments. In: Weske, M., Montali, M., Weber, I., vom Brocke, J. (eds.) BPM 2018. LNCS, vol. 11080, pp. 215–232. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-98648-7_13
Weijters, A., van der Aalst, W.M.P., De Medeiros, A.A.: Process mining with the heuristics miner-algorithm, pp. 1–34. Technical report WP 166, Technische Universiteit Eindhoven (2006)
van Zelst, S.J., Bolt, A., Hassani, M., van Dongen, B.F., van der Aalst, W.M.P.: Online conformance checking: relating event streams to process models using prefix-alignments. Int. J. Data Sci. Anal. 8(3), 269–284 (2019). https://doi.org/10.1007/s41060-017-0078-6
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We thank the Alexander von Humboldt (AvH) Stiftung for supporting our research.
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Berti, A., van der Aalst, W.M.P. (2021). A Novel Token-Based Replay Technique to Speed Up Conformance Checking and Process Enhancement. In: Koutny, M., Kordon, F., Pomello, L. (eds) Transactions on Petri Nets and Other Models of Concurrency XV. Lecture Notes in Computer Science(), vol 12530. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-63079-2_1
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