Advertisement

Proposal of an Inference Engine Architecture for Business Rules and Processes

  • Grzegorz J. Nalepa
  • Krzysztof Kluza
  • Krzysztof Kaczor
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7895)

Abstract

In this paper, we discuss a new architecture for integrating and executing business process models with rules. It is based on a workflow engine that runs a BPMN-based business process model. On the lower level, rules are used to express the specific parts of the business logic. Rules working in the same context are grouped into a single task in the process model. Such a rule task is modeled by a formally defined decision table, which is designed in a visual way and its quality can be formally verified. In the runtime environment, tables are executed by a dedicated rule inference engine controlled by a workflow engine.

Keywords

Business Process Inference Engine Decision Table Prototype Implementation Business Rule 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Nalepa, G.J., Kluza, K.: UML representation for rule-based application models with XTT2-based business rules. International Journal of Software Engineering and Knowledge Engineering (IJSEKE) 22(4), 485–524 (2012)CrossRefGoogle Scholar
  2. 2.
    Ross, R.G.: Principles of the Business Rule Approach, 1st edn. Addison-Wesley Professional (2003)Google Scholar
  3. 3.
    von Halle, B.: Business Rules Applied: Building Better Systems Using the Business Rules Approach. Wiley (2001)Google Scholar
  4. 4.
    Buchanan, B.G., Shortliffe, E.H. (eds.): Rule-Based Expert Systems. Addison-Wesley Publishing Company, Reading (1985)Google Scholar
  5. 5.
    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 Reviews: Data Mining and Knowledge Discovery 1(2), 117–137 (2011)CrossRefGoogle Scholar
  6. 6.
    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)CrossRefGoogle Scholar
  7. 7.
    Charfi, A., Mezini, M.: Hybrid web service composition: Business processes md,,eet business rules. In: Proceedings of the 2nd International Conference on Service-Oriented Computing, ICSOC 2004, pp. 30–38. ACM, New York (2004)Google Scholar
  8. 8.
    OMG: Semantics of Business Vocabulary and Business Rules (SBVR). Technical Report dtc/06-03-02, Object Management Group (2006)Google Scholar
  9. 9.
    OMG: Business Process Model and Notation (BPMN): Version 2.0 specification. Technical Report formal/2011-01-03, Object Management Group (January 2011)Google Scholar
  10. 10.
    Adams, M., ter Hofstede, A.H.M., Edmond, D., van der Aalst, W.M.P.: Worklets: A service-oriented implementation of dynamic flexibility in workflows. In: Meersman, R., Tari, Z. (eds.) OTM 2006. LNCS, vol. 4275, pp. 291–308. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  11. 11.
    Milanovic, M., Gaševic, D.: Towards a language for rule-enhanced business process modeling. In: Proceedings of the 13th IEEE International Conference on Enterprise Distributed Object Computing, EDOC 2009, pp. 59–68. IEEE Press, Piscataway (2009)Google Scholar
  12. 12.
    van Eijndhoven, T., Iacob, M.E., Ponisio, M.: Achieving business process flexibility with business rules. In: Proceedings of the 12th International IEEE Enterprise Distributed Object Computing Conference, EDOC 2008, pp. 95–104 (September 2008)Google Scholar
  13. 13.
    Kluza, K., Kaczor, K., Nalepa, G.J.: Enriching business processes with rules using the oryx BPMN editor. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part II. LNCS, vol. 7268, pp. 573–581. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  14. 14.
    Nalepa, G.J., Ligęza, A.: HeKatE methodology, hybrid engineering of intelligent systems. International Journal of Applied Mathematics and Computer Science 20(1), 35–53 (2010)CrossRefGoogle Scholar
  15. 15.
    Baumeister, J., Freiberg, M.: Knowledge visualization for evaluation tasks. Knowledge and Information Systems 29(2), 349–378 (2011)CrossRefGoogle Scholar
  16. 16.
    Nalepa, G.J.: Proposal of business process and rules modeling with the XTT method. In: Negru, V. (ed.) Symbolic and Numeric Algorithms for Scientific Computing, SYNASC Ninth International Symposium, September 26-29, vol. 506, pp. 500–506. IEEE Computer Society, IEEE, CPS Conference Publishing Service, Los Alamitos, California (2007)CrossRefGoogle Scholar
  17. 17.
    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, Karlsruhe, Germany, September 21, pp. 6–17 (2010)Google Scholar
  18. 18.
    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., et al. (eds.) Intelligent Distributed Computing V. SCI, vol. 382, pp. 249–255. Springer, Heidelberg (2011)Google Scholar
  19. 19.
    Hollingsworth, D.: The workflow reference model. Issue 1.1 TC00-1003, Workflow Management Coalition (January 1995)Google Scholar
  20. 20.
    Hu, J., Zhao, Z., Lv, Z.: Implementation of process management and control based on jbpm4.4. In: 2011 Second International Conference on Networking and Distributed Computing (ICNDC), pp. 218–221 (September 2011)Google Scholar
  21. 21.
    Huang, Y.Y., Jiang, R., Li, H.: A reusable system architecture based on jbpm and its application. In: Zhang, Y. (ed.) Future Communication, Computing, Control and Management. LNEE, vol. 142, pp. 517–525. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  22. 22.
    Bing, H., Dan-Mei, X.: Research and design of document flow model based on JBPM workflow engine. In: Proceedings from International Forum on Computer Science-Technology and Applications, IFCSTA 2009, vol. 1, pp. 336–339 (December 2009)Google Scholar
  23. 23.
    Peng, L., Zhou, B.: Research on workflow patterns based on jBPM and jPDL. In: Proceedings from IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008, pp. 838–843. IEEE (December 2008)Google Scholar
  24. 24.
    Wohed, P., Russell, N., ter Hofstede, A.H., Andersson, B., van der Aalst, W.M.: Patterns-based evaluation of open source BPM systems: The cases of jBPM, OpenWFE, and Enhydra Shark. Information and Software Technology 51(8), 1187–1216 (2009)CrossRefGoogle Scholar
  25. 25.
    Ostermayer, L., Seipel, D.: Knowledge engineering for business rules in prolog. In: Proceedings of the 26th Workshop on Logic Programming (WLP 2012), Bonn, Germany, September 24-25. CoRR Computing Research Repository (2012)Google Scholar
  26. 26.
    Nalepa, G.J.: Semantic Knowledge Engineering. A Rule-Based Approach. Wydawnictwa AGH, Kraków (2011)Google Scholar
  27. 27.
    Nalepa, G., Bobek, S., Ligęza, A., Kaczor, K.: Algorithms for rule inference in modularized rule bases. In: Bassiliades, N., Governatori, G., Paschke, A. (eds.) RuleML 2011 - Europe. LNCS, vol. 6826, pp. 305–312. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  28. 28.
    Nalepa, G.J., Bobek, S., Ligęza, A., Kaczor, K.: HalVA - rule analysis framework for XTT2 rules. In: Bassiliades, N., Governatori, G., Paschke, A. (eds.) RuleML 2011 - Europe. LNCS, vol. 6826, pp. 337–344. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  29. 29.
    Nalepa, G.J., Ligęza, A., Kaczor, K.: Formalization and modeling of rules using the XTT2 method. International Journal on Artificial Intelligence Tools 20(6), 1107–1125 (2011)CrossRefGoogle Scholar
  30. 30.
    Nalepa, G.J.: Architecture of the heaRT hybrid rule engine. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part II. LNCS, vol. 6114, pp. 598–605. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  31. 31.
    Sekuła, R.: Review of selected workflow environments. Technical report, AGH UST, BSc Thesis, G.J.Nalepa, PhD Supervisor (2012)Google Scholar
  32. 32.
    Denvir, T., Oliveira, J., Plat, N.: The Cash-Point (ATM) ’Problem’. Formal Aspects of Computing 12(4), 211–215 (2000)CrossRefGoogle Scholar
  33. 33.
    Müller, R., Greiner, U., Rahm, E.: Agent work: a workflow system supporting rule-based workflow adaptation. Data Knowl. Eng. 51(2), 223–256 (2004)CrossRefGoogle Scholar
  34. 34.
    Goedertier, S., Vanthienen, J.: Business rules for compliant business process models. In: Abramowicz, W., Mayr, H.C. (eds.) BIS. LNI, vol. 85, pp. 558–572. GI (2006)Google Scholar
  35. 35.
    Rosenberg, F., Rosenberg, F., Dustdar, S., Dustdar, S.: Business rules integration in BPEL – a service-oriented approach. In: Proceedings of the 7th International IEEE Conference on E-Commerce Technology (CEC 2005), pp. 476–479 (July 2005)Google Scholar
  36. 36.
    zur Muehlen, M., Indulska, M., Kamp, G.: Business process and business rule modeling languages for compliance management: a representational analysis. In: Tutorials, Posters, Panels and Industrial Contributions at the 26th International Conference on Conceptual Modeling - Volume 83. ER ’07, Darlinghurst, Australia, Australia, Australian Computer Society, Inc. (2007) 127–132Google Scholar
  37. 37.
    zur Muehlen, M., Indulska, M., Kittel, K.: Towards integrated modeling of business processes and business rules. In: 19th Australasian Conference on Information Systems ACIS 2008, Christchurch, New Zealand (December 2008)Google Scholar
  38. 38.
    Di Bona, D., Lo Re, G., Aiello, G., Tamburo, A., Alessi, M.: A methodology for graphical modeling of business rules. In: 5th UKSim European Symposium on Computer Modeling and Simulation (EMS) 2011, pp. 102–106 (November 2011)Google Scholar
  39. 39.
    Kluza, K., Maślanka, T., Nalepa, G.J., Ligęza, A.: Proposal of representing BPMN diagrams with XTT2-based business rules. In: Brazier, F.M. (ed.) et al., eds.: Intelligent Distributed Computing V. Proceedings of the 5th International Symposium on Intelligent Distributed Computing – IDC 2011, Delft, the Netherlands, Oct. 2011. Studies in Computational Intelligence, vol. 382, pp. 243–248. Springer, Heidelberg (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Grzegorz J. Nalepa
    • 1
  • Krzysztof Kluza
    • 1
  • Krzysztof Kaczor
    • 1
  1. 1.AGH University of Science and TechnologyKrakowPoland

Personalised recommendations