Business Process Recomposition as a Way to Redesign Workflows Effectively
Piotr Wiśniewski, Krzysztof Kluza, Paweł Jemioło, Antoni Ligęza, Anna Suchenia
Citation: Proceedings of the 16th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 25, pages 471–474 (2021)
Abstract. Business process models are subject to changing requirements. The purpose of this paper is to present methods that enable computer-aided recomposition of process models, understood as using existing processes to design new ones. This procedure involves dividing existing BPMN diagrams into smaller components, from which new models can be created. This kind of model generation can be performed manually by the user or run automatically, based on the Constraint Programming technique. The presented algorithms can improve the process of model redesign and allow users to avoid typical anomalies that may occur in the modeling phase.
- M. Pondel and J. Pondel, “Selected it tools in enterprise knowledge management processes–overview and efficiency study,” in IFIP International Workshop on Artificial Intelligence for Knowledge Management. Springer, 2017, pp. 12–28.
- H. Leopold, J. Mendling, and O. Günther, “Learning from quality issues of BPMN models from industry,” IEEE software, vol. 33, no. 4, pp. 26–33, 2015.
- P. Wiśniewski, “Decomposition of business process models into reusable sub-diagrams,” in ITM Web of Conferences, vol. 15. EDP Sciences, 2017, p. 01002.
- P. Wiśniewski, K. Kluza, M. Ślażyński, and A. Ligęza, “Constraint-based composition of business process models,” in International Conference on Business Process Management. Springer, 2017, pp. 133–141.
- M. Dumas, L. García-Bañuelos, M. La Rosa, and R. Uba, “Fast detection of exact clones in business process model repositories,” Information Systems, vol. 38, no. 4, pp. 619–633, 2013.
- F. M. Maggi, A. J. Mooij, and W. M. van der Aalst, “User-guided discovery of declarative process models,” in 2011 IEEE symposium on computational intelligence and data mining (CIDM). IEEE, 2011, pp. 192–199.
- M. Skouradaki, V. Andrikopoulos, and F. Leymann, “Representative BPMN 2.0 process model generation from recurring structures,” in 2016 IEEE International Conference on Web Services (ICWS). IEEE, 2016, pp. 468–475.
- A. Suchenia, T. Potempa, A. Ligęza, K. Jobczyk, and K. Kluza, “Selected approaches towards taxonomy of business process anomalies,” in Advances in Business ICT: New Ideas from Ongoing Research. Springer, 2017, pp. 65–85.
- I. M. Weber, Semantic Methods for Execution-level Business Process Modeling: Modeling Support Through Process Verification and Service Composition. Springer, 2009, vol. 40.
- B. Van Dongen, R. Dijkman, and J. Mendling, “Measuring similarity between business process models,” in Seminal Contributions to Information Systems Engineering. Springer, 2013, pp. 405–419.
- R. Klimek and P. Szwed, “Verification of ArchiMate process specifications based on deductive temporal reasoning,” in 2013 Federated Conference on Computer Science and Information Systems. IEEE, 2013, pp. 1109–1116.
- R. Chenouard, L. Granvilliers, and R. Soto, “Model-driven constraint programming,” in Proceedings of the 10th international ACM SIGPLAN conference on Principles and practice of declarative programming, 2008, pp. 236–246.