Abstract
The alignment of observed and modeled behavior is an essential element for organizations, since it opens the door for conformance checking and enhancement of processes. The state-of-the-art technique for computing alignments has exponential time and space complexity, hindering its applicability for medium and large instances. In this article, a novel approach is presented to tackle the challenge of computing an alignment for large-problem instances that correspond to well-formed process models. Given an observed trace, first it uses a novel replay technique to find an initial candidate trace in the model. Then a local search framework is applied to try to improve the alignment until no further improvement is possible. The implementation of the presented technique reveals a magnificent reduction both in computation time and in memory usage. Moreover, although the proposed technique does not guarantee the derivation of an alignment with minimal cost, the experiments show that in practice the quality of the obtained solutions is close to optimal.
- 2018. 4TU: Centre for Research Data. http://researchdata.4tu.nl/homGoogle Scholar
- Arya Adriansyah. 2014. Aligning Observed and Modeled Behavior. Ph.D. Dissertation. Technische Universiteit Eindhoven.Google Scholar
- Andrea Burattin. 2016. PLG2: Multiperspective process randomization with online and offline simulations. In Proceedings of the BPM Demo Track 2016 Co-located with the 14th International Conference on Business Process Management (BPM 2016), Rio de Janeiro, Brazil, September 21, 2016. 1--6. http://ceur-ws.org/Vol-1789/bpm-demo-2016-paper1.pdf.Google Scholar
- Josep Carmona, Boudewijn F. van Dongen, Andreas Solti, and Matthias Weidlich. 2018. Conformance Checking - Relating Processes and Models. Springer. DOI:https://doi.org/10.1007/978-3-319-99414-7Google Scholar
- Massimiliano de Leoni and Andrea Marrella. 2017. Aligning real process executions and prescriptive process models through automated planning. Expert Syst. Appl. 82 (2017), 162--183.Google ScholarDigital Library
- J. Desel and J. Esparza. 1993. Reachability in cyclic extended free-choice systems. TCS 114. Elsevier Science Publishers B.V. (1993).Google Scholar
- J. Desel and J. Esparza. 1995. Free Choice Petri Nets. Cambridge University Press, Cambridge, Great Britain.Google Scholar
- J. Esparza and S. Melzer. 2000. Verification of safety properties using integer programming: Beyond the state equation. Formal Methods in System Design 16 (2000), 159--189.Google ScholarDigital Library
- Luciano García-Bañuelos, Nick R. T. P. van Beest, Marlon Dumas, Marcello La Rosa, and Willem Mertens. 2018. Complete and interpretable conformance checking of business processes. IEEE Transactions on Software Engineering 44, 3 (March 2018), 262--290. DOI:https://doi.org/10.1109/TSE.2017.2668418Google ScholarDigital Library
- Gurobi Optimization, Inc. 2016. Gurobi Optimizer Reference Manual. http://www.gurobi.com.Google Scholar
- R. P. Jagadeesh Chandra Bose and Wil van der Aalst. 2010. Trace Alignment in Process Mining: Opportunities for Process Diagnostics. Springer Berlin, Berlin,, 227--242. DOI:https://doi.org/10.1007/978-3-642-15618-2_17Google Scholar
- Kristian Bisgaard Lassen and Wil M. P. van der Aalst. 2009. Complexity metrics for workflow nets. Inf. Softw. Technol. 51, 3 (March 2009), 610--626. DOI:https://doi.org/10.1016/j.infsof.2008.08.005Google ScholarDigital Library
- Sander J. J. Leemans, Dirk Fahland, and Wil M. P. van der Aalst. 2018. Scalable process discovery and conformance checking. Software and System Modeling 17, 2 (2018), 599--631.Google ScholarDigital Library
- Jorge Munoz-Gama, Josep Carmona, and Wil M. P. Van Der Aalst. 2014. Single-entry single-exit decomposed conformance checking. Inf. Syst. 46 (Dec. 2014), 102--122. DOI:https://doi.org/10.1016/j.is.2014.04.003Google Scholar
- T. Murata. 1989. Petri nets: Properties, analysis and applications. Proc. IEEE 77, 4 (April 1989), 541--574.Google ScholarCross Ref
- Richard Neapolitan. 2014. Foundations of Algorithms (5th ed.). Jones and Bartlett Publishers, Inc., USA, 138--146.Google Scholar
- Saul B. Needleman and Christian D. Wunsch. 1970. A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of Molecular Biology 48, 3 (1970), 443--453. DOI:https://doi.org/10.1016/0022-2836(70)90057-4Google ScholarCross Ref
- Artem Polyvyanyy, Wil M. P. van der Aalst, Arthur H. M. ter Hofstede, and Moe Thandar Wynn. 2017. Impact-driven process model repair. ACM Trans. Softw. Eng. Methodol. 25, 4 (2017), 28:1–28:60. DOI:https://doi.org/10.1145/2980764Google ScholarDigital Library
- Daniel Reißner, Raffaele Conforti, Marlon Dumas, Marcello La Rosa, and Abel Armas-Cervantes. 2017. Scalable conformance checking of business processes. (March 2017). http://eprints.qut.edu.au/105118/ Paper submitted to “International Conference on Business Process Management (BMP 2017)” in Barcelona, Spain.Google Scholar
- Anne Rozinat and Wil M. P. van der Aalst. 2008. Conformance checking of processes based on monitoring real behavior. Inf. Syst. 33, 1 (2008), 64--95. DOI:https://doi.org/10.1016/j.is.2007.07.001Google ScholarDigital Library
- M. Silva, E. Teruel, and J. M. Colom. 1998. Linear algebraic and linear programming techniques for the analysis of place/transition net systems. In Lecture Notes in Computer Science: Lectures on Petri Nets I: Basic Models, W. Reisig and G. Rozenberg (Eds.). Vol. 1491. Springer-Verlag, 309--373.Google Scholar
- Farbod Taymouri. 2017. ALI: Alignment for Large Instances. https://www.cs.upc.edu/taymouri/tool.html.Google Scholar
- Farbod Taymouri and Josep Carmona. 2016a. A recursive paradigm for aligning observed behavior of large structured process models. In Proceedings of the 14th International Conference of Business Process Management (BPM), (Rio de Janeiro, Brazil, September 18-22).Google ScholarCross Ref
- Farbod Taymouri and Josep Carmona. 2016b. Model and event log reductions to boost the computation of alignments. In Proceedings of the 6th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2016), (Graz, Austria, December 15-16, 2016). 50--62. http://ceur-ws.org/Vol-1757/paper4.pdf.Google Scholar
- Wil M. P. van der Aalst. 2013. Decomposing petri nets for process mining: A generic approach. Distributed and Parallel Databases 31, 4 (2013), 471--507. DOI:https://doi.org/10.1007/s10619-013-7127-5Google ScholarDigital Library
- Wil M. P. van der Aalst. 2016. Process Mining - Data Science in Action, Second Edition. Springer. DOI:https://doi.org/10.1007/978-3-662-49851-4Google ScholarDigital Library
- Wil M. P. van der Aalst, Kees M. van Hee, Arthur H. M. ter Hofstede, Natalia Sidorova, H. M. W. Verbeek, Marc Voorhoeve, and Moe Thandar Wynn. 2011. Soundness of workflow nets: Classification, decidability, and analysis. Formal Asp. Comput. 23, 3 (2011), 333--363. DOI:https://doi.org/10.1007/s00165-010-0161-4Google ScholarDigital Library
- Boudewijn van Dongen, Josep Carmona, Thomas Chatain, and Farbod Taymouri. 2017. Aligning modeled and observed behavior: A compromise between complexity and quality. In Proceedings of the 29th International Conference on Advanced Information Systems Engineering (CAiSE’17) (Lecture Notes in Computer Science), Eric Dubois and Klaus Pohl (Eds.), Vol. 10253. Springer, Cham.Google ScholarCross Ref
- Boudewijn F. van Dongen. 2018. Efficiently computing alignments - using the extended marking equation. In Proceedings of the 16th International Conference on Business Process Management, (BPM 2018), (Sydney, NSW, Australia, September 9-14, 2018). 197--214. DOI:https://doi.org/10.1007/978-3-319-98648-7_12Google Scholar
- B. F. van Dongen, A. K. A. de Medeiros, H. M. W. Verbeek, A. J. M. M. Weijters, and W. M. P. van der Aalst. 2005. The prom framework: A new era in process mining tool support. In Proceedings of the 26th International Conference on Applications and Theory of Petri Nets (ICATPN’05). Springer-Verlag, Berlin, 444--454. DOI:https://doi.org/10.1007/11494744_25Google Scholar
- Seppe K. L. M. vanden Broucke, Jochen De Weerdt, Jan Vanthienen, and Bart Baesens. 2014. Determining process model precision and generalization with weighted artificial negative events. IEEE Trans. Knowl. Data Eng. 26, 8 (2014), 1877--1889. DOI:https://doi.org/10.1109/TKDE.2013.130Google ScholarCross Ref
- H. M. W. Verbeek and W. M. P. van der Aalst. 2016. Merging Alignments for Decomposed Replay. Springer International Publishing, Cham, 219--239. DOI:https://doi.org/10.1007/978-3-319-39086-4_14Google Scholar
Index Terms
- Computing Alignments of Well-Formed Process Models using Local Search
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