Abstract
Business processes drive the value creation at companies requiring them to constantly monitor and improve the former. The field of Process Comparison (PC) offers promising approaches to gain insight into differences between variants of a process that one can leverage to improve the latter. For example, one might consider the same process at different points in time or at different sites. Recent PC methods consider event logs containing data on real-life process executions the single source of truth. However, there often exist additional specifications that can be represented as Petri nets. In this paper, we propose an approach that leverages a given Petri net to compare two event logs in a hierarchical manner. To this end, we decompose the provided net into subprocesses and extract data on their executions from the event logs. Based on these executions, we exemplify how one can flexibly assess different aspects of a process (e.g., control flow, performance, or conformance). Using statistical tests, we eventually detect differences between subprocesses with respect to a selected aspect. Despite the approach is mostly agnostic to the decomposition applied, we present a decomposition strategy that we deem particularly suitable for PC. For this purpose, we consider the ned Process Structure Tree of a Petri net and propose a novel preprocessing approach to improve the final decomposition. We implemented the approach in ProM and evaluate it in a real-life case study.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
van der Aalst, W.M.P., de Medeiros, A.K.A., Weijters, A.J.M.M.: Process equivalence: comparing two process models based on observed behavior. In: Dustdar, S., Fiadeiro, J.L., Sheth, A.P. (eds.) BPM 2006. LNCS, vol. 4102, pp. 129–144. Springer, Heidelberg (2006). https://doi.org/10.1007/11841760_10
van der Aalst, W.M.P.: Decomposing Petri nets for process mining: a generic approach. Distrib. Parallel Databases 31(4), 471–507 (2013). https://doi.org/10.1007/s10619-013-7127-5
van der Aalst, W.M.P., Stahl, C.: Information systems. In: Modeling Business Processes: A Petri Net-Oriented Approach (2011). https://doi.org/10.7551/mitpress/8811.003.0003
van der Aalst, W.M.P., Tacke Genannt Unterberg, D., Denisov, V., Fahland, D.: Visualizing token flows using interactive performance spectra. In: Janicki, R., Sidorova, N., Chatain, T. (eds.) PETRI NETS 2020. LNCS, vol. 12152, pp. 369–380. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-51831-8_18
Adriansyah, A., van Dongen, B.F., van der Aalst, W.M.P.: Towards robust conformance checking. In: zur Muehlen, M., Su, J. (eds.) BPM 2010. LNBIP, vol. 66, pp. 122–133. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-20511-8_11
Andrews, K., Wohlfahrt, M., Wurzinger, G.: Visual graph comparison. In: 13th International Conference Information Visualisation, pp. 62–67 (2009). https://doi.org/10.1109/IV.2009.108
van Beest, N.R.T.P., Dumas, M., GarcÃa-Bañuelos, L., La Rosa, M.: Log delta analysis: interpretable differencing of business process event logs. In: Motahari-Nezhad, H.R., Recker, J., Weidlich, M. (eds.) BPM 2015. LNCS, vol. 9253, pp. 386–405. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23063-4_26
Bolt, A., de Leoni, M., van der Aalst, W.M.P.: A visual approach to spot statistically-significant differences in event logs based on process metrics. In: Nurcan, S., Soffer, P., Bajec, M., Eder, J. (eds.) CAiSE 2016. LNCS, vol. 9694, pp. 151–166. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39696-5_10
Bouvier, P., Garavel, H., Ponce-de-León, H.: Automatic decomposition of Petri nets into automata networks – a synthetic account. In: Janicki, R., Sidorova, N., Chatain, T. (eds.) PETRI NETS 2020. LNCS, vol. 12152, pp. 3–23. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-51831-8_1
Cecconi, A., Augusto, A., Di Ciccio, C.: Detection of statistically significant differences between process variants through declarative rules. In: Polyvyanyy, A., Wynn, M.T., Van Looy, A., Reichert, M. (eds.) BPM 2021. LNBIP, vol. 427, pp. 73–91. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-85440-9_5
Cohen, J.: Statistical Power Analysis for the Behavioral Sciences, chap. 2, 2nd edn., pp. 20–27 (1988). https://doi.org/10.4324/9780203771587
Cordes, C., Vogelgesang, T., Appelrath, H.-J.: A generic approach for calculating and visualizing differences between process models in multidimensional process mining. In: Fournier, F., Mendling, J. (eds.) BPM 2014. LNBIP, vol. 202, pp. 383–394. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-15895-2_32
Eshuis, R.: Translating safe Petri nets to statecharts in a structure-preserving way. In: Cavalcanti, A., Dams, D.R. (eds.) FM 2009. LNCS, vol. 5850, pp. 239–255. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-05089-3_16
Ivanov, S.Y., Kalenkova, A.A., van der Aalst, W.M.P.: BPMNDiffViz: a tool for BPMN models comparison. BPM reports 1507 (2015)
Johnson, R., Pearson, D., Pingali, K.: The program structure tree: computing control regions in linear time. In: Proceedings of the ACM SIGPLAN 1994 Conference on Programming Language Design and Implementation, pp. 171–185 (1994). https://doi.org/10.1145/773473.178258
Karatkevich, A., Andrzejewski, G.: Hierarchical decomposition of Petri nets for digital microsystems design. In: 2006 International Conference - Modern Problems of Radio Engineering, Telecommunications, and Computer Science, pp. 518–521 (2006). https://doi.org/10.1109/TCSET.2006.4404613
Kriglstein, S., Wallner, G., Rinderle-Ma, S.: A visualization approach for difference analysis of process models and instance traffic. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 219–226. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40176-3_18
Küster, J.M., Gerth, C., Förster, A., Engels, G.: Detecting and resolving process model differences in the absence of a change log. In: Dumas, M., Reichert, M., Shan, M.-C. (eds.) BPM 2008. LNCS, vol. 5240, pp. 244–260. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-85758-7_19
de Leoni, M., Mannhardt, F.: Road traffic fine management process (2015). https://doi.org/10.4121/uuid:270fd440-1057-4fb9-89a9-b699b47990f5
Munoz-Gama, J., Carmona, J., van der Aalst, W.M.P.: Hierarchical conformance checking of process models based on event logs. In: Colom, J.-M., Desel, J. (eds.) PETRI NETS 2013. LNCS, vol. 7927, pp. 291–310. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38697-8_16
Munoz-Gama, J., Carmona, J., van der Aalst, W.M.P.: Single-entry single-exit decomposed conformance checking. Inf. Syst. 46, 102–122 (2014). https://doi.org/10.1016/j.is.2014.04.003
Nguyen, H., Dumas, M., La Rosa, M., ter Hofstede, A.H.M.: Multi-perspective comparison of business process variants based on event logs. In: Trujillo, J.C., et al. (eds.) ER 2018. LNCS, vol. 11157, pp. 449–459. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00847-5_32
Pini, A., Brown, R., Wynn, M.T.: Process visualization techniques for multi-perspective process comparisons. In: Bae, J., Suriadi, S., Wen, L. (eds.) AP-BPM 2015. LNBIP, vol. 219, pp. 183–197. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19509-4_14
Polyvyanyy, A., Vanhatalo, J., Völzer, H.: Simplified computation and generalization of the refined process structure tree. In: Bravetti, M., Bultan, T. (eds.) WS-FM 2010. LNCS, vol. 6551, pp. 25–41. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-19589-1_2
Taymouri, F., La Rosa, M., Carmona, J.: Business process variant analysis based on mutual fingerprints of event logs. In: Dustdar, S., Yu, E., Salinesi, C., Rieu, D., Pant, V. (eds.) CAiSE 2020. LNCS, vol. 12127, pp. 299–318. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-49435-3_19
Taymouri, F., Rosa, M.L., Dumas, M., Maggi, F.M.: Business process variant analysis: survey and classification. Knowl.-Based Syst. 211, 106557 (2021). https://doi.org/10.1016/j.knosys.2020.106557
Vanhatalo, J., Völzer, H., Koehler, J.: The refined process structure tree. In: Dumas, M., Reichert, M., Shan, M.-C. (eds.) BPM 2008. LNCS, vol. 5240, pp. 100–115. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-85758-7_10
Vidgof, M., Djurica, D., Bala, S., Mendling, J.: Interactive log-delta analysis using multi-range filtering. Softw. Syst. Model. 21, 847–868 (2022). https://doi.org/10.1007/s10270-021-00902-0
Welch, B.L.: The generalization of ‘student’s’ problem when several different population variances are involved. Biometrika 34(1–2), 28–35 (1947). https://doi.org/10.1093/biomet/34.1-2.28
Wynn, M.T., et al.: ProcessProfiler3D: a visualisation framework for log-based process performance comparison. Decis. Support Syst. 100, 93–108 (2017). https://doi.org/10.1016/j.dss.2017.04.004
van Zelst, S.J., van Dongen, B.F., van der Aalst, W.M.P.: ILP-based process discovery using hybrid regions. In: Algorithms & Theories for the Analysis of Event Data, pp. 47–61. CEUR Workshop Proceedings (2015)
Zhong, C., He, W., Li, Z., Wu, N., Qu, T.: Deadlock analysis and control using petri net decomposition techniques. Inf. Sci. 482, 440–456 (2019). https://doi.org/10.1016/j.ins.2019.01.029
Acknowledgments
Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy-EXC-2023 Internet of Production-390621612. We also thank the Alexander von Humboldt (AvH) Stiftung for supporting our research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Brockhoff, T., Gose, M.N., Uysal, M.S., van der Aalst, W.M.P. (2024). Process Comparison Using Petri Net Decomposition. In: Kristensen, L.M., van der Werf, J.M. (eds) Application and Theory of Petri Nets and Concurrency. PETRI NETS 2024. Lecture Notes in Computer Science, vol 14628. Springer, Cham. https://doi.org/10.1007/978-3-031-61433-0_5
Download citation
DOI: https://doi.org/10.1007/978-3-031-61433-0_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-61432-3
Online ISBN: 978-3-031-61433-0
eBook Packages: Computer ScienceComputer Science (R0)