Understanding the Occurrence of Errors in Process Models Based on Metrics

  • Jan Mendling
  • Gustaf Neumann
  • Wil van der Aalst
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4803)


Business process models play an important role for the management, design, and improvement of process organizations and process-aware information systems. Despite the extensive application of process modeling in practice, there are hardly empirical results available on quality aspects of process models. This paper aims to advance the understanding of this matter by analyzing the connection between formal errors (such as deadlocks) and a set of metrics that capture various structural and behavioral aspects of a process model. In particular, we discuss the theoretical connection between errors and metrics, and provide a comprehensive validation based on an extensive sample of EPC process models from practice. Furthermore, we investigate the capability of the metrics to predict errors in a second independent sample of models. The high explanatory power of the metrics has considerable consequences for the design of future modeling guidelines and modeling tools.


Business Process Quality Aspect Business Process Modeling Articulation Point Quality Framework 
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.


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  1. 1.
    Lindland, O.I., Sindre, G., Sølvberg, A.: Understanding quality in conceptual modeling. IEEE Software 11, 42–49 (1994)CrossRefGoogle Scholar
  2. 2.
    Becker, J., Rosemann, M., Uthmann, C.: Guidelines of Business Process Modeling. In: van der Aalst, W., Desel, J., Oberweis, A. (eds.) Business Process Management. Models, Techniques, and Empirical Studies, pp. 30–49. Springer, Berlin (2000)Google Scholar
  3. 3.
    Hoppenbrouwers, S.S., Proper, H.E., van der Weide, T.: A Fundamental View on the Process of Conceptual Modeling. In: Delcambre, L.M.L., Kop, C., Mayr, H.C., Mylopoulos, J., Pastor, Ó. (eds.) ER 2005. LNCS, vol. 3716, pp. 128–143. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  4. 4.
    Krogstie, J., Sindre, G., Jørgensen, H.: Process models representing knowledge for action: a revised quality framework. European Journal of Information Systems 15, 91–102 (2006)CrossRefGoogle Scholar
  5. 5.
    Moody, D.: Theoretical and practical issues in evaluating the quality of conceptual models: current state and future directions. Data & Knowledge Engineering 55, 243–276 (2005)CrossRefGoogle Scholar
  6. 6.
    Davies, I., Green, P., Rosemann, M., Indulska, M., Gallo, S.: How do practitioners use conceptual modeling in practice? Data & Knowledge Engineering 58, 358–380 (2006)CrossRefGoogle Scholar
  7. 7.
    Mendling, J., Moser, M., Neumann, G., Verbeek, H., Dongen, B., van der Aalst, W.: Faulty EPCs in the SAP Reference Model. In: Dustdar, S., Fiadeiro, J.L., Sheth, A. (eds.) BPM 2006. LNCS, vol. 4102, pp. 451–457. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  8. 8.
    Mendling, J., Moser, M., Neumann, G., Verbeek, H., Dongen, B., van der Aalst, W.: Detection and Prediction of Errors in EPCs of the SAP Reference Model. Data & Knowledge Engineering (accepted for publication)Google Scholar
  9. 9.
    Simon, H.: Sciences of the Artificial, 3rd edn. The MIT Press, Cambridge (1996)Google Scholar
  10. 10.
    Mendling, J., Neumann, G.: Error metrics for business process models. Technical Report JM-2006-12-03, Vienna Univ. of Econ. and Business Administration (2006)Google Scholar
  11. 11.
    Keller, G., Nüttgens, M., Scheer, A.W.: Semantische Prozessmodellierung auf der Grundlage “Ereignisgesteuerter Prozessketten (EPK)”. Heft 89, Institut für Wirtschaftsinformatik, Saarbrücken, Germany (1992)Google Scholar
  12. 12.
    OMG, (ed.): Business Process Modeling Notation (BPMN) Specification. Final Adopted Specification, dtc/06-02-01, Object Management Group (2006)Google Scholar
  13. 13.
    van der Aalst, W., ter Hofstede, A.: YAWL: Yet Another Workflow Language. Information Systems 30, 245–275 (2005)CrossRefGoogle Scholar
  14. 14.
    Mendling, J., van der Aalst, W.: Formalization and Verification of EPCs with OR-Joins Based on State and Context. In: CAiSE 2007. Proceedings of the 19th Conference on Advanced Information Systems Engineering (2007)Google Scholar
  15. 15.
    van Dongen, B., Medeiros, A., Verbeek, H., Weijters, A., van der Aalst, W.: The ProM framework: A New Era in Process Mining Tool Support. In: Ciardo, G., Darondeau, P. (eds.) ICATPN 2005. LNCS, vol. 3536, pp. 444–454. Springer, Heidelberg (2005)Google Scholar
  16. 16.
    Mendling, J.: Detection and Prediction of Errors in EPC Business Process Models. PhD thesis, Vienna University of Economics and Business Administration (2007)Google Scholar
  17. 17.
    Mendling, J., Nüttgens, M.: EPC Markup Language (EPML) - An XML-Based Interchange Format for Event-Driven Process Chains (EPC). Information Systems and e-Business Management 4, 245–263 (2006)CrossRefGoogle Scholar
  18. 18.
    Nüttgens, M., Rump, F.J.: Syntax und Semantik Ereignisgesteuerter Prozessketten (EPK). In: Desel, J., Weske, M. (eds.) Proceedings of Promise 2002, Potsdam, Germany. Lecture Notes in Informatics, vol. 21, pp. 64–77 (2002)Google Scholar
  19. 19.
    Keller, G., Teufel, T.: SAP(R) R/3 Process Oriented Implementation: Iterative Process Prototyping. Addison-Wesley, Reading (1998)Google Scholar
  20. 20.
    Tukey, J.: Exploratory Data Analysis. Addison-Wesley, Reading (1977)zbMATHGoogle Scholar
  21. 21.
    Judge, G., Hill, R., Griffiths, W., Lütkepohl, H., Lee, T.C.: Introduction to the theory and practice of econometrics, 2nd edn. John Wiley & Sons, England (1988)zbMATHGoogle Scholar
  22. 22.
    Hosmer, D., Lemeshow, S.: Applied Logistic Regression. Wiley & Sons, England (2000)zbMATHGoogle Scholar
  23. 23.
    Marczyk, G., DeMatteo, D., Festinger, D.: Essentials of Research Design and Methodology. Wiley & Sons, Inc., England (2005)Google Scholar
  24. 24.
    Becker, J., Schütte, R.: Handelsinformationssysteme. Moderne Industrie (2004)Google Scholar
  25. 25.
    Scheer, A.-W.: Wirtschaftsinformatik: Referenzmodelle für industrielle Geschäfts-prozesse. Springer, Heidelberg (1998)Google Scholar
  26. 26.
    Seidlmeier, H.: Prozessmodellierung mit ARIS. Vieweg Verlag (2002)Google Scholar
  27. 27.
    Staud, J.: Geschäftsprozessanalyse: Ereignisgesteuerte Prozessketten und Objektorientierte Geschäftsprozessmodellierung. Springer, Heidelberg (2006)Google Scholar
  28. 28.
    Reisig, W., Rozenberg, G. (eds.): Lectures on Petri Nets I: Basic Models. LNCS, vol. 1491. Springer, Heidelberg (1998)zbMATHGoogle Scholar
  29. 29.
    Moody, D., Sindre, G., Brasethvik, T., Sølvberg, A.: Evaluating the quality of process models: Empirical testing of a quality framework. In: Spaccapietra, S., March, S.T., Kambayashi, Y. (eds.) ER 2002. LNCS, vol. 2503, pp. 380–396. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  30. 30.
    ISO: Information technology - software product evaluation - quality characteristics and guide lines for their use. Iso/iec is 9126 (1991)Google Scholar
  31. 31.
    Güceglioglu, A.S., Demirörs, O.: Using software quality characteristics to measure business process quality. In: van der Aalst, W.M.P., Benatallah, B., Casati, F., Curbera, F. (eds.) BPM 2005. LNCS, vol. 3649, pp. 374–379. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  32. 32.
    Lee, G., Yoon, J.M.: An empirical study on the complexity metrics of petri nets. Microelectronics and Reliability 32, 323–329 (1992)CrossRefGoogle Scholar
  33. 33.
    Nissen, M.: Redesigning reengineering through measurement-driven inference. MIS Quarterly 22, 509–534 (1998)CrossRefGoogle Scholar
  34. 34.
    Morasca, S.: Measuring attributes of concurrent software specifications in petri nets. In: METRICS 1999. Proceedings of the 6th International Symposium on Software Metrics, pp. 100–110. IEEE Computer Society Press, Washington, DC, USA (1999)Google Scholar
  35. 35.
    Reijers, H., Vanderfeesten, I.: Cohesion and coupling metrics for workflow process design. In: Desel, J., Pernici, B., Weske, M. (eds.) BPM 2004. LNCS, vol. 3080, pp. 290–305. Springer, Heidelberg (2004)Google Scholar
  36. 36.
    Cardoso, J.: Evaluating Workflows and Web Process Complexity. In: Workflow Handbook 2005, Future Strategies Inc., 284–290 (2005)Google Scholar
  37. 37.
    Balasubramanian, S., Gupta, M.: Structural metrics for goal based business process design and evaluation. Business Process Management Journal 11, 680–694 (2005)CrossRefGoogle Scholar
  38. 38.
    Canfora, G., García, F., Piattini, M., Ruiz, F., Visaggio, C.: A family of experiments to validate metrics for software process models. Journal of Systems and Software 77, 113–129 (2005)CrossRefGoogle Scholar
  39. 39.
    Aguilar, E.R., Ruiz, F., García, F., Piattini, M.: Towards a Suite of Metrics for Business Process Models in BPMN. In: Manolopoulos, Y., Filipe, J., Constantopoulos, P., Cordeiro, J. (eds.) ICEIS 2006. Proceedings of the Eighth International Conference on Enterprise Information Systems: Databases and Information Systems Integration (III), Paphos, Cyprus, May 23-27, 2006, pp. 440–443 (2006)Google Scholar
  40. 40.
    Laue, R., Gruhn, V.: Complexity metrics for business process models. In: Abramowicz, W., Mayr, H.C. (eds.) BIS 2006. 9th International Conference on Business Information Systems. Lecture Notes in Informatics, vol. 85, pp. 1–12 (2006)Google Scholar
  41. 41.
    Cardoso, J.: Process control-flow complexity metric: An empirical validation. In: IEEE SCC 2006. Proceedings of IEEE International Conference on Services Computing, Chicago, USA, September 18-22, pp. 167–173. IEEE Computer Society Press, Los Alamitos (2006)Google Scholar
  42. 42.
    Rosemann, M., Recker, J., Indulska, M., Green, P.: A study of the evolution of the representational capabilities of process modeling grammars. In: Dubois, E., Pohl, K. (eds.) CAiSE 2006. LNCS, vol. 4001, pp. 447–461. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  43. 43.
    Agarwal, R., Sinha, A.P.: Object-oriented modeling with UML: a study of developers’ perceptions. Commun. ACM 46, 248–256 (2003)CrossRefGoogle Scholar
  44. 44.
    Sarshar, K., Loos, P.: Comparing the control-flow of epc and petri net from the end-user perspective. In: van der Aalst, W.M.P., Benatallah, B., Casati, F., Curbera, F. (eds.) BPM 2005. LNCS, vol. 3649, pp. 434–439. Springer, Heidelberg (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Jan Mendling
    • 1
  • Gustaf Neumann
    • 2
  • Wil van der Aalst
    • 3
  1. 1.BPM Cluster, Faculty of Information Technology, Queensland University of TechnologyAustralia
  2. 2.Institute of Information Systems and New Media, Vienna University of Economics and Business AdministrationAustria
  3. 3.Department of Computer Science, Eindhoven University of TechnologyThe Netherlands

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