Formalized Integration of Rules and Processes

  • Grzegorz J. NalepaEmail author
Part of the Intelligent Systems Reference Library book series (ISRL, volume 130)


In this chapter a formalized model for describing the integration of business processes with business rules is discussed. The solution uses the existing representation methods for processes and rules, specifically the Business Process Model and Notation (BPMN) for process models, and the XTT method for rules. The proposed model deals with the integration of processes with rules in order to provide a coherent formal description, and to support the practical design. Furthermore, in such an approach, BP can be used as a high level inference control for the XTT knowledge base. The chapter provides a formal description of a BPMN process model. This formalized process model is then integrated with rules, and this integration is specified as the General Business Logic Model. In order to apply this model to a specific rule solution, the Specific Business Logic Model is presented. As an evaluation, a case study described using the proposed model is presented.


  1. 1.
    Lindsay, A., Dawns, D., Lunn, K.: Business processes – attempts to find a definition. Inf. Software Technol. 45(15), 1015–1019 (2003). ElsevierGoogle Scholar
  2. 2.
    Charfi, A., Mezini, M.: Hybrid web service composition: business processes meet business rules. In: Proceedings of the 2nd International Conference on Service-Oriented Computing, ICSOC 2004, New York, NY, USA. ACM, pp. 30–38 (2004)Google Scholar
  3. 3.
    Knolmayer, G., Endl, R., Pfahrer, M.: Modeling processes and workflows by business rules. In: Business Process Management, Models, Techniques, and Empirical Studies, pp. 16–29. Springer, London (2000)Google Scholar
  4. 4.
    Kluza, K., Nalepa, G.J., Łysik, Ł.: Visual inference specification methods for modularized rulebases. Overview and integration proposal. In: Nalepa, G.J., Baumeister, J. (eds.) Proceedings of the 6th Workshop on Knowledge Engineering and Software Engineering (KESE6) at the 33rd German Conference on Artificial Intelligence, 21 September 2010, Karlsruhe, Germany, pp. 6–17 (2010)Google Scholar
  5. 5.
    Hohwiller, J., Schlegel, D., Grieser, G., Hoekstra, Y.: Integration of bpm and brm. In: Dijkman, R., Hofstetter, J., Koehler, J. (eds.) Business Process Model and Notation. Lecture Notes in Business Information Processing, vol. 95, pp. 136–141. Springer, Berlin (2011)CrossRefGoogle Scholar
  6. 6.
    OMG: Business Process Model and Notation (BPMN): Version 2.0 specification. Technical report formal/2011-01-03, Object Management Group, January 2011Google Scholar
  7. 7.
    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
  8. 8.
    Wagner, G., Giurca, A., Lukichev, S.: R2ml: a general approach for marking up rules. In: Bry, F., Fages, F., Marchiori, M., Ohlbach, H. (eds.) Principles and Practices of Semantic Web Reasoning, Dagstuhl Seminar Proceedings 05371 (2005)Google Scholar
  9. 9.
    Object Management Group (OMG): Decision model and notation request for proposal. Technical report bmi/2011-03-04, Object Management Group, 140 Kendrick Street, Building A Suite 300, Needham, MA 02494, USA, March 2011Google Scholar
  10. 10.
    Kluza, K.: Methods for Modeling and Integration of Business Processes with Rules. Ph.D. thesis, AGH University of Science and Technology, Supervisor: Grzegorz J. Nalepa, March 2015Google Scholar
  11. 11.
    Nalepa, G.J., Kluza, K., Kaczor, K.: Proposal of an inference engine architecture for business rules and processes. In: Rutkowski, L., et al. (eds.) Artificial Intelligence and Soft Computing: 12th International Conference, ICAISC 2013, Zakopane, Poland, 9–13 June 2013, vol. 7895. Lecture Notes in Artificial Intelligence, pp. 453–464. Springer, Berlin (2013)Google Scholar
  12. 12.
    Ligęza, A.: Intelligent data and knowledge analysis and verification; towards a taxonomy of specific problems. In: Vermesan, A., Coenen, F. (eds.) Validation and Verification of Knowledge Based Systems, pp. 313–325. Springer, US (1999)CrossRefGoogle Scholar
  13. 13.
    Nalepa, G., Bobek, S., Ligęza, A., Kaczor, K.: HalVA – rule analysis framework for XTT2 rules. In: Bassiliades, N., Governatori, G., Paschke, A. (eds.) Rule-Based Reasoning, Programming, and Applications, vol. 6826. Lecture Notes in Computer Science, pp. 337–344. Springer, Berlin (2011)Google Scholar
  14. 14.
    Wynn, M., Verbeek, H., van der Aalst, W., Hofstede, A., Edmond, D.: Business process verification - finally a reality!. Bus. Process Manag. J. 1(15), 74–92 (2009)CrossRefGoogle Scholar
  15. 15.
    Szpyrka, M., Nalepa, G.J., Ligęza, A., Kluza, K.: Proposal of formal verification of selected BPMN models with Alvis modeling language. In: Brazier, F.M., Nieuwenhuis, K., Pavlin, G., Warnier, M., Badica, C. (eds.) Intelligent Distributed Computing V. Proceedings of the 5th International Symposium on Intelligent Distributed Computing – IDC 2011, Delft, The Netherlands – October 2011, vol. 382. Studies in Computational Intelligence, pp. 249–255. Springer, Berlin (2011)Google Scholar
  16. 16.
    Kluza, K., Nalepa, G. J.: Formal Model of Business Processes Integrated with Business Rules. Information Systems Frontiers (2016, submitted)Google Scholar
  17. 17.
    Kluza, K., Nalepa, G.J.: Automatic generation of business process models based on attribute relationship diagrams. In: Lohmann, N., Song, M., Wohed, P. (eds.) Business Process Management Workshops, vol. 171. Lecture Notes in Business Information Processing, pp. 185–197. Springer International Publishing, Berlin (2014)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.AGH University of Science and TechnologyKrakówPoland

Personalised recommendations