Advertisement

A Multi-level Hierarchical Approach for Configuring Business Processes

  • Mateusz Baran
  • Krzysztof KluzaEmail author
  • Grzegorz J. Nalepa
  • Antoni Ligęza
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 579)

Abstract

Business Process configuration constitutes a powerful tool for expressing similarities between different Business Process models. Such models in the case of real life systems are often very complex. Configuration gives the opportunity to keep different models in a single configurable model. Another approach to manage model complexity is hierarchization, which allows for encapsulating process details into sub-levels, helps to avoid inconsistencies and fosters reuse of similar parts of models. In this paper, we present an approach for configuring Business Processes that is based on hierarchization. Our approach takes advantage of the arbitrary \(n\)-to-\(m\) relationships between tasks in the merged processes. It preserves similar abstraction level of subprocesses in a hierarchy and allows a user to grasp the high-level flow of the merged processes. We also describe how to extend the approach to support multi-level hierarchization.

Keywords

Business Process Configurable Model Business Process Model Hierarchization Algorithm Merge Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors wish to thank the organizers of the ABICT 2013 workshop on the FedCSIS 2013 conference for providing an ample environment for presenting and discussing our research.

References

  1. 1.
    OMG: Business Process Model and Notation (BPMN): Version 2.0 specification. Technical report formal/2011-01-03, Object Management Group (2011)Google Scholar
  2. 2.
    Allweyer, T.: BPMN 2.0. Introduction to the Standard for Business Process Modeling. BoD, Norderstedt (2010)Google Scholar
  3. 3.
    Nalepa, G.J., Kluza, K.: UML representation for rule-based application models with XTT2-based business rules. Int. J. Softw. Eng. Knowl. Eng. (IJSEKE) 22(4), 485–524 (2012). http://www.worldscientific.com/doi/abs/10.1142/S021819401250012X
  4. 4.
    Silver, B.: BPMN Method and Style. Cody-Cassidy Press (2009)Google Scholar
  5. 5.
    Reijers, H., Mendling, J., Dijkman, R.: Human and automatic modularizations of process models to enhance their comprehension. Inf. Syst. 36(5), 881–897 (2011)CrossRefGoogle Scholar
  6. 6.
    Mendling, J., Reijers, H.A., van der Aalst, W.M.P.: Seven process modeling guidelines (7PMG). Inf. Softw. Technol. 52(2), 127–136 (2010)Google Scholar
  7. 7.
    Yan, Z., Dijkman, R., Grefen, P.: Business process model repositories—framework and survey. Inf. Softw. Technol. 54(4), 380–395 (2012)CrossRefGoogle Scholar
  8. 8.
    Dijkman, R., Dumas, M., van Dongen, B., Käärik, R., Mendling, J.: Similarity of business process models: metrics and evaluation. Information Systems 36(2), 498–516 (2011)CrossRefGoogle Scholar
  9. 9.
    Baran, M., Kluza, K., Nalepa, G.J., Ligęza, A.: A hierarchical approach for configuring business processes. In: Ganzha, M., Maciaszek, L.A.,Paprzycki, M. (eds.) Proceedings of the Federated Conference on Computer Science and Information Systems—FedCSIS 2013, Krakow, Poland, 8–11 September 2013, pp. 931–937. IEEE (2013)Google Scholar
  10. 10.
    Nuffel, D.V., Backer, M.D.: Multi-abstraction layered business process modeling. Comput. Ind. 63(2), 131–147 (2012)CrossRefGoogle Scholar
  11. 11.
    Pittke, F., Leopold, H., Mendling, J., Tamm, G.: Enabling reuse of process models through the detection of similar process parts. In: La Rosa, M., Soffer, P. (eds.) Business Process Management Workshops. Lecture Notes in Business Information Processing, vol. 132, pp. 586–597. Springer, Berlin (2013)CrossRefGoogle Scholar
  12. 12.
    Weber, B., Reichert, M., Mendling, J., Reijers, H.A.: Refactoring large process model repositories. Comput. Ind. 62(5), 467–486 (2011)CrossRefGoogle Scholar
  13. 13.
    La Rosa, M., Wohed, P., Mendling, J., ter Hofstede, A., Reijers, H., Van der Aalst, W.M.P.: Managing process model complexity via abstract syntax modifications. Ind. Inf. IEEE Trans. 7(4), 614–629 (2011)CrossRefGoogle Scholar
  14. 14.
    Cappelli, C., Leite, J.C., Batista, T., Silva, L.: An aspect-oriented approach to business process modeling. In: Proceedings of the 15th Workshop on Early Aspects. EA’09, pp. 7–12. ACM, New York (2009)Google Scholar
  15. 15.
    Dumas, M., Garcia-Banuelos, L., Rosa, M.L., Uba, R.: Fast detection of exact clones in business process model repositories. Inf. Syst. 38(4), 619–633 (2013)CrossRefGoogle Scholar
  16. 16.
    Uba, R., Dumas, M., Garcia-Banuelos, L., Rosa, M.: Clone detection in repositories of business process models. In: Rinderle-Ma, S., Toumani, F., Wolf, K. (eds.) Business Process Management. Lecture Notes in Computer Science, vol. 6896, pp. 248–264. Springer, Berlin (2011)CrossRefGoogle Scholar
  17. 17.
    Haddar, N.Z., Makni, L., Ben Abdallah, H.: Literature review of reuse in business process modeling. Softw. Syst. Model. 121, 1–15 (2012)Google Scholar
  18. 18.
    Mendling, J., Neumann, G., Aalst, W.: Understanding the occurrence of errors in process models based on metrics. In: Meersman, R., Tari, Z. (eds.) On the Move to Meaningful Internet Systems 2007: CoopIS, DOA, ODBASE, GADA, and IS. Lecture Notes in Computer Science, vol. 4803, pp. 113–130. Springer, Berlin (2007)Google Scholar
  19. 19.
    Dijkman, R., Rosa, M.L., Reijers, H.A.: Managing large collections of business process models—current techniques and challenges. Comput. Ind. 63(2), 91–97 (2012)CrossRefGoogle Scholar
  20. 20.
    Kunze, M., Weske, M.: Metric trees for efficient similarity search in large process model repositories. In: Muehlen, M., Su, J. (eds.) Business Process Management Workshops. Lecture Notes in Business Information Processing, vol. 66, pp. 535–546. Springer, Berlin Heidelberg (2011)CrossRefGoogle Scholar
  21. 21.
    La Rosa, M., Gottschalk, F.: Synergia-comprehensive tool support for configurable process models. In: Proceedings of the Demo Track of the 7th International Conference on Business Process Management (BPM’09), vol. 489. CEUR (2009)Google Scholar
  22. 22.
    Bobek, S., Baran, M., Kluza, K., Nalepa, G.J.: Application of bayesian networks to recommendations in business process modeling. In: Giordano, L., Montani, S., Dupre, D.T. (eds.) Proceedings of the Workshop AI Meets Business Processes 2013 co-located with the 13th Conference of the Italian Association for Artificial Intelligence (AI*IA 2013), Turin, Italy, December 6, 2013 (2013). http://ceur-ws.org/Vol-1101/
  23. 23.
    van der Aalst, W.M.: Business process management: a comprehensive survey. In: ISRN Software Engineering 2013 (2013)Google Scholar
  24. 24.
    La Rosa, M., Dumas, M., ter Hofstede, A.H., Mendling, J.: Configurable multi-perspective business process models. Inf. Syst. 36(2), 313–340 (2011)CrossRefGoogle Scholar
  25. 25.
    Rosemann, M., van der Aalst, W.M.P.: A configurable reference modelling language. Inf. Syst. 32(1), 1–23 (2007)CrossRefGoogle Scholar
  26. 26.
    Puhlmann, F., Schnieders, A., Weiland, J., Weske, M.: Variability Mechanisms for Process Models. PESOA-Report TR 17/2005, Process Family Engineering in Service-Oriented Applications (pesoa). BMBF-Project. Report, Hasso Plattner Institut, Postdam, Germany (2005)Google Scholar
  27. 27.
    Schnieders, A., Puhlmann, F.: Variability mechanisms in e-business process families. In: Proceeedings of the International Conference on Business Information Systems (BIS 2006), pp. 583–601 (2006)Google Scholar
  28. 28.
    Tealeb, A., Awad, A., Galal-Edeen, G.: Context-based variant generation of business process models. In: Bider, I., Gaaloul, K., Krogstie, J., Nurcan, S., Proper, H.A., Schmidt, R., Soffer, P. (eds.) Enterprise, Business-Process and Information Systems Modeling, no. 175 in Lecture Notes in Business Information Processing, pp. 363–377. Springer, Berlin (2014). http://link.springer.com/chapter/10.1007/978-3-662-43745-2_25
  29. 29.
    La Rosa, M., Dumas, M., Uba, R., Dijkman, R.M.: Business process model merging: an approach to business process consolidation. ACM Trans. Softw. Eng. Methodol. (TOSEM) 22(2), 11 (2013)Google Scholar
  30. 30.
    Döhring, M., Reijers, H.A., Smirnov, S.: Configuration vs. adaptation for business process variant maintenance: an empirical study. Inf. Syst. 39, 108–133 (2014)CrossRefGoogle Scholar
  31. 31.
    Weidmann, M., Koetter, F., Kintz, M., Schleicher, D., Mietzner, R.: Adaptive business process modeling in the internet of services (ABIS). In: ICIW 2011, The Sixth International Conference on Internet and Web Applications and Services, pp. 29–34 (2011)Google Scholar
  32. 32.
    Müller, R., Greiner, U., Rahm, E.: Agentwork: a workflow system supporting rule-based workflow adaptation. Data Knowl. Eng. 51(2), 223–256 (2004)CrossRefGoogle Scholar
  33. 33.
    Charfi, A., Müller, H., Mezini, M.: Aspect-oriented business process modeling with ao4bpmn. In: Modelling Foundations and Applications, pp. 48–61. Springer, Heidelberg (2010)Google Scholar
  34. 34.
    Rastrepkina, M.: Managing variability in process models by structural decomposition. In: Business Process Modeling Notation, pp. 106–113. Springer (2011)Google Scholar
  35. 35.
    Gottschalk, F., Van Der Aalst, W.M., Jansen-Vullers, M.H., La Rosa, M.: Configurable workflow models. Int. J. Co-op. Inf. Syst. 17(02), 177–221 (2008)CrossRefGoogle Scholar
  36. 36.
    Awad, A., Sakr, S., Kunze, M., Weske, M.: Design by selection: a reuse-based approach for business process modeling. In: Conceptual Modeling-ER 2011, pp. 332–345. Springer, Berlin (2011)Google Scholar
  37. 37.
    Meerkamm, S.: Configuration of multi-perspectives variants. In: Business Process Management Workshops, pp. 277–288. Springer, Heidelberg (2011)Google Scholar
  38. 38.
    Meerkamm, S.: Staged configuration of multi-perspectives variants based on a generic data model. In: Business Process Management Workshops, pp. 326–337. Springer, Heidelberg (2012)Google Scholar
  39. 39.
    Hallerbach, A., Bauer, T., Reichert, M.: Capturing variability in business process models: the provop approach. J. Softw. Maint. Evol. Res. Pract. 22(6–7), 519–546 (2010)Google Scholar
  40. 40.
    Döhring, M., Zimmermann, B.: vBPMN: Event-Aware Workflow Variants by Weaving BPMN2 and Business Rules. In: Enterprise, Business-Process and Information Systems Modeling, pp. 332–341. Springer (2011)Google Scholar
  41. 41.
    Nalepa, G.J.: Proposal of business process and rules modeling with the XTT method. In: V. Negru, et al. (eds.) Symbolic and numeric algorithms for scientific computing, 2007. SYNASC Ninth international symposium. September 26–29, pp. 500–506. IEEE Computer Society, IEEE, CPS Conference Publishing Service, Los Alamitos, California; Washington; Tokyo (2007)Google Scholar
  42. 42.
    Ligęza, A., Nalepa, G.J.: A study of methodological issues in design and development of rule-based systems: proposal of a new approach. Wiley Interdisciplinary Rev. Data Mining Knowl. Discov. 1(2), 117–137 (2011). doi: 10.1002/widm.11
  43. 43.
    Nalepa, G.J., Ligęza, A., Kaczor, K.: Formalization and modeling of rules using the XTT2 method. Int. J. Artif. Intell. Tools 20(6), 1107–1125 (2011)CrossRefGoogle Scholar
  44. 44.
    Nalepa, G., Bobek, S., Ligęza, A., Kaczor, K.: Algorithms for rule inference in modularized rule bases. In: Bassiliades, N., Governatori, G., Paschke, A. (eds.) Rule-Based Reasoning, Programming, and Applications. Lecture Notes in Computer Science, vol. 6826, pp. 305–312. Springer, Berlin / Heidelberg (2011)CrossRefGoogle Scholar
  45. 45.
    Kluza, K., Nalepa, G.J.: Proposal of square metrics for measuring business process model complexity. In: M. Ganzha, L.A. Maciaszek, M. Paprzycki (eds.) Proceedings of the Federated Conference on Computer Science and Information Systems—FedCSIS 2012, Wroclaw, Poland, 9–12 September 2012, pp. 919–922 (2012). http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6354395

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Mateusz Baran
    • 1
    • 2
  • Krzysztof Kluza
    • 1
    Email author
  • Grzegorz J. Nalepa
    • 1
  • Antoni Ligęza
    • 1
  1. 1.AGH University of Science and TechnologyKrakowPoland
  2. 2.Cracow University of TechnologyKrakowPoland

Personalised recommendations