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RoSE: Reoccurring Structures Detection in BPMN 2.0 Process Model Collections

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On the Move to Meaningful Internet Systems: OTM 2016 Conferences (OTM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10033))

Abstract

The detection of structural similarities of process models is frequently discussed in the literature. The state-of-the-art approaches for structural similarities of process models presume a known subgraph that is searched in a larger graph, and utilize behavioral and textual semantics to achieve their goal. In this paper we propose an approach to detect reoccurring structures in a collection of BPMN 2.0 process models, without the knowledge of a subgraph to be searched, and by focusing solely on the structural characteristics of the process models. The proposed approach deals with the problems of subgraph isomorphism, frequent pattern discovery and maximum common subgraph isomorphism, which are mentioned as NP-hard in the literature. In this work we present a formal model and a novel algorithm for the detection of reoccurring structures in a collection of BPMN 2.0 process models. We then apply the algorithm to a collection of 1,806 real-world process models and provide a quantitative and qualitative analysis of the results.

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Notes

  1. 1.

    http://www.iaas.uni-stuttgart.de/forschung/projects/benchflow.php.

  2. 2.

    https://github.com/marigianna-iaas/RoSE.

  3. 3.

    http://www.eclipse.org/modeling/mdt/?project=bpmn2.

  4. 4.

    https://github.com/marigianna-iaas/RoSE.

  5. 5.

    http://www-01.ibm.com/software/data/industry-models/.

  6. 6.

    http://bpmai.org/.

References

  1. van der Aalst, W.M.P., et al.: Workflow patterns. Distrib. Parallel Databases 14(1), 5–51 (2003)

    Article  Google Scholar 

  2. Breuker, D., Delfmann, P., Dietrich, H.A., Steinhorst, M.: Graph theory and model collection management: conceptual framework and runtime analysis of selected graph algorithms. Inf. Syst. e-Bus. Manag. 13(1), 69–106 (2014)

    Article  Google Scholar 

  3. Burattin, A.: Process Mining Techniques in Business Environments. LNBIP, vol. 207. Springer, Heidelberg (2015)

    Google Scholar 

  4. Cordella, L.P., et al.: A (sub)graph isomorphism algorithm for matching large graphs. IEEE Trans. Pattern Anal. Mach. Intell. 26(10), 1367–1372 (2004)

    Article  Google Scholar 

  5. Dijkman, R.M., et al.: Similarity of business process models: metrics and evaluation. Inf. Syst. 36(2), 498–516 (2011)

    Article  Google Scholar 

  6. Dijkman, R.M., et al.: A short survey on process model similarity. In: Bubenko, J., Krogstie, J., Pastor, O., Pernici, B., Rolland, C., Sølvberg, A. (eds.) Seminal Contributions to Information Systems Engineering, pp. 421–427. Springer, Heidelberg (2013). doi:10.1007/978-3-642-36926-1_34

    Chapter  Google Scholar 

  7. Dumas, M., et al.: Fast detection of exact clones in business process model repositories. Inf. Syst. 38(4), 619–633 (2013)

    Article  Google Scholar 

  8. Ekanayake, C.C., Rosa, M., Hofstede, A.H.M., Fauvet, M.-C.: Fragment-based version management for repositories of business process models. In: Meersman, R., Dillon, T., Herrero, P., Kumar, A., Reichert, M., Qing, L., Ooi, B.-C., Damiani, E., Schmidt, D.C., White, J., Hauswirth, M., Hitzler, P., Mohania, M. (eds.) OTM 2011. LNCS, vol. 7044, pp. 20–37. Springer, Heidelberg (2011). doi:10.1007/978-3-642-25109-2_3

    Chapter  Google Scholar 

  9. Ekanayake, C.C., Dumas, M., García-Bañuelos, L., Rosa, M., Hofstede, A.H.M.: Approximate clone detection in repositories of business process models. In: Barros, A., Gal, A., Kindler, E. (eds.) BPM 2012. LNCS, vol. 7481, pp. 302–318. Springer, Heidelberg (2012). doi:10.1007/978-3-642-32885-5_24

    Chapter  Google Scholar 

  10. Feitelson, D.G.: Workload Modeling for Computer Systems Performance Evaluation. Cambridge University Press, New York (2015)

    Book  MATH  Google Scholar 

  11. Ferme, V., et al.: A container-centric methodology for benchmarking workflow management systems. In: Proceedings of CLOSER 2016. Springer, Heidelberg (2016)

    Google Scholar 

  12. Grossmann, W., Rinderle-Ma, S.: Fundamentals of Business Intelligence. Data-Centric Systems and Applications. Springer, Heidelberg (2015)

    Book  Google Scholar 

  13. Gupta, A., Nishimura, N.: The Complexity of Subgraph Isomorphism: Duality Results for Graphs of Bounded Path- and Tree-Width. Technical Report CS-95-14. Univ. of Waterloo, Comp. Sc. Dep., Waterloo, Ontario, Canada (1995)

    Google Scholar 

  14. Hertis, M., Juric, M.: An empirical analysis of business process execution language usage. IEEE Trans. Softw. Eng. 40(8), 738–757 (2014)

    Article  Google Scholar 

  15. Ivanov, S., et al.: BPMNDiffViz: a tool for bpmn models comparison. In: BPM (Demos). CEUR-WS.org (2015)

    Google Scholar 

  16. Jordan, D., Evdemon, J.: Business Process Model And Notation (BPMN) version 2.0. Object Management Group, Inc. http://www.omg.org/spec/BPMN/2.0/

  17. La Rosa, M., et al.: APROMORE: an advanced process model repository. Expert Syst. Appl. 38(6), 7029–7040 (2011)

    Article  Google Scholar 

  18. Muehlen, M., Recker, J.: How much language is enough? theoretical and practical use of the business process modeling notation. In: Bellahsène, Z., Léonard, M. (eds.) CAiSE 2008. LNCS, vol. 5074, pp. 465–479. Springer, Heidelberg (2008). doi:10.1007/978-3-540-69534-9_35

    Chapter  Google Scholar 

  19. Nijssen, S., Kok, J.N.: The gaston tool for frequent subgraph mining. Electron. Notes Theor. Comput. Sci. 127(1), 77–87 (2005)

    Article  MathSciNet  Google Scholar 

  20. OASIS: Web Services Business Process Execution Language Version 2.0 - OASIS Standard (2007)

    Google Scholar 

  21. Pietsch, P., Wenzel, S.: Comparison of BPMN2 diagrams. In: Mendling, J., Weidlich, M. (eds.) BPMN 2012. LNBIP, vol. 125, pp. 83–97. Springer, Heidelberg (2012). doi:10.1007/978-3-642-33155-8_7

    Chapter  Google Scholar 

  22. Pittke, F., Leopold, H., Mendling, J., Tamm, G.: Enabling reuse of process models through the detection of similar process parts. In: Rosa, M., Soffer, P. (eds.) BPM 2012. LNBIP, vol. 132, pp. 586–597. Springer, Heidelberg (2013). doi:10.1007/978-3-642-36285-9_59

    Chapter  Google Scholar 

  23. 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). doi:10.1007/978-3-642-19589-1_2

    Chapter  Google Scholar 

  24. Schumm, D., et al.: Integrating compliance into business processes: process fragments as reusable compliance controls. In: MKWI (2010)

    Google Scholar 

  25. Skouradaki, M., Leymann, F.: Detecting frequently recurring structures in BPMN 2.0 process models. In: SummerSOC. IBM (2015)

    Google Scholar 

  26. Skouradaki, M., et al.: Application of sub-graph isomorphism to extract reoccurring structures from BPMN 2.0 process models. In: Proceedings of SOSE 2015. IEEE (2015)

    Google Scholar 

  27. Skouradaki, M., et al.: On the road to benchmarking BPMN 2.0 workflow engines. In: IProceedings of ICPE 2015 (2015)

    Google Scholar 

  28. Ullmann, J.R.: An algorithm for subgraph isomorphism. ACM 23(1), 31–42 (1976)

    Article  MathSciNet  Google Scholar 

  29. Valiente, G.: Algorithms on Trees and Graphs. Springer, Berlin (2002)

    Book  MATH  Google Scholar 

  30. Valiente, G., Martínez, C.: An algorithm for graph pattern-matching. In: South American Workshop on String Processing. Carleton University Press (1997)

    Google Scholar 

  31. Yan, X., Han, J.: gSpan: graph-based substructure pattern mining. In: Proceedings of ICDM 2002. Institute of Electrical & Electronics Engineers (IEEE) (2002)

    Google Scholar 

  32. Yan, Z., Dijkman, R., Grefen, P.: Generating synthetic process model collections with properties of labeled real-life models. In: Ouyang, C., Jung, J.-Y. (eds.) AP-BPM 2014. LNBIP, vol. 181, pp. 74–88. Springer, Heidelberg (2014). doi:10.1007/978-3-319-08222-6_6

    Google Scholar 

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Acknowledgments

This work is funded by the “BenchFlow – A Benchmark for Workflow Management Systems” project DACH Grant No. 200021E-145062/1 and by the “SmartOrchestra” (01MD16001F) project funded by the BMWi.

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Authors and Affiliations

  1. IAAS, University of Stuttgart, Stuttgart, Germany

    Marigianna Skouradaki, Vasilios Andrikopoulos & Frank Leymann

  2. IPVS, University of Stuttgart, Stuttgart, Germany

    Oliver Kopp

Authors
  1. Marigianna Skouradaki
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  2. Vasilios Andrikopoulos
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  3. Oliver Kopp
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  4. Frank Leymann
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Corresponding author

Correspondence to Marigianna Skouradaki .

Editor information

Editors and Affiliations

  1. ADAPT Centre, Trinity College Dublin, Dublin 2, Ireland

    Christophe Debruyne

  2. University of Lorraine, Vandoeuvre-les-Nancy, France

    Hervé Panetto

  3. TU Graz, Graz, Austria

    Robert Meersman

  4. La Trobe University, Melbourne, Australia

    Tharam Dillon

  5. Institute of Computer Languages, TU Wien, Vienna, Austria

    eva Kühn

  6. ADAPT Centre, Trinity College Dublin, Dublin 2, Ireland

    Declan O'Sullivan

  7. Università degli Studi di Milano Crema, Crema, Italy

    Claudio Agostino Ardagna

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Skouradaki, M., Andrikopoulos, V., Kopp, O., Leymann, F. (2016). RoSE: Reoccurring Structures Detection in BPMN 2.0 Process Model Collections. In: Debruyne, C., et al. On the Move to Meaningful Internet Systems: OTM 2016 Conferences. OTM 2016. Lecture Notes in Computer Science(), vol 10033. Springer, Cham. https://doi.org/10.1007/978-3-319-48472-3_15

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  • DOI: https://doi.org/10.1007/978-3-319-48472-3_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48471-6

  • Online ISBN: 978-3-319-48472-3

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