Application of Fuzzy Logic to Assess the Quality of BPMN Models

  • Fadwa YahyaEmail author
  • Khouloud Boukadi
  • Hanêne Ben-Abdallah
  • Zakaria Maamar
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 868)


Modeling is the first stage in a Business Process’s (BP) lifecycle. A high-quality BP model is vital to the successful implementation, execution, and monitoring stages. Different works have evaluated BP models from a quality perspective. These works either used formal verification or a set of quality metrics. This paper adopts quality metric and targets models represented in Business Process Modeling and Notation (BPMN). It proposes an approach based on fuzzy logic along with a tool system developed under eclipse framework. The preliminary experimental evaluation of the proposed system shows encouraging results.


Business Process BPMN Model quality Quality metrics Fuzzy logic 


  1. 1.
    Bender, R.: Quantitative risk assessment in epidemiological studies investigating threshold effects. Biom. J. 41(3), 305–319 (1999)CrossRefGoogle Scholar
  2. 2.
    Cardoso, J., Mendling, J., Neumann, G., Reijers, H.A.: A discourse on complexity of process models. In: Eder, J., Dustdar, S. (eds.) BPM 2006. LNCS, vol. 4103, pp. 117–128. Springer, Heidelberg (2006). Scholar
  3. 3.
    Cardoso, J., Vanderfeesten, I., Reijers, H.A.: Computing coupling for business process models (2010). Accessed 20 Sept 2012
  4. 4.
    Curtis, B., Kellner, M.I., Over, J.: Process modeling. Commun. ACM 35(9), 75–90 (1992)CrossRefGoogle Scholar
  5. 5.
    Guceglioglu, A.S., Demirors, 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). Scholar
  6. 6.
    Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. ACM SIGKDD Explor. Newsl. 11(1), 10–18 (2009)CrossRefGoogle Scholar
  7. 7.
    Hanley, J.A., McNeil, B.J.: The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143(1), 29–36 (1982)CrossRefGoogle Scholar
  8. 8.
    Heinrich, R.: Aligning business process quality and information system quality. Ph.D. thesis (2013)Google Scholar
  9. 9.
    ISO: ISO/IEC 25010:2011 - systems and software engineering - systems and software quality requirements and evaluation (square) - system and software quality models (2011). Accessed 08 Dec 2016
  10. 10.
    ISO: ISO/IEC 19510:2013 - information technology - object management group business process model and notation (2013). Accessed 17 Oct 2016
  11. 11.
    Makni, L., Khlif, W., Haddar, N.Z., Ben-Abdallah, H.: A tool for evaluating the quality of business process models. In: ISSS/BPSC, pp. 230–242. Citeseer (2010)Google Scholar
  12. 12.
    Mendling, J.: Testing density as a complexity metric for EPCs. In: German EPC Workshop on Density of Process Models (2006)Google Scholar
  13. 13.
    Mendling, J., Reijers, H.A., van der Aalst, W.M.: Seven process modeling guidelines (7PMG). Inf. Softw. Technol. 52(2), 127–136 (2010)CrossRefGoogle Scholar
  14. 14.
    Mendling, J., Sánchez-González, L., Garcia, F., La Rosa, M.: Thresholds for error probability measures of business process models. J. Syst. Softw. 85(5), 1188–1197 (2012)CrossRefGoogle Scholar
  15. 15.
    Morimoto, S.: A survey of formal verification for business process modeling. In: Bubak, M., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds.) ICCS 2008. LNCS, vol. 5102, pp. 514–522. Springer, Heidelberg (2008). Scholar
  16. 16.
    Muketha, G., Ghani, A., Selamat, M., Atan, R.: A survey of business process complexity metrics. Inf. Technol. J. 9(7), 1336–1344 (2010)CrossRefGoogle Scholar
  17. 17.
    de Oca, I.M.M., Snoeck, M., Reijers, H.A., Rodríguez-Morffi, A.: A systematic literature review of studies on business process modeling quality. Inf. Softw. Technol. 58, 187–205 (2015)CrossRefGoogle Scholar
  18. 18.
    Quinlan, J.R.: Induction of decision trees. Mach. Learn. 1(1), 81–106 (1986)Google Scholar
  19. 19.
    Reijers, H.A., Vanderfeesten, I.T.P.: 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). Scholar
  20. 20.
    Sadowska, M.: An approach to assessing the quality of business process models expressed in BPMN. e-Inf. Softw. Eng. J. 9(1), 57–77 (2015)Google Scholar
  21. 21.
    Safavian, S.R., Landgrebe, D.: A survey of decision tree classifier methodology. IEEE Trans. Syst. Man Cybern. 21(3), 660–674 (1991)MathSciNetCrossRefGoogle Scholar
  22. 22.
    Sánchez-González, L., García, F., Mendling, J., Ruiz, F.: Quality assessment of business process models based on thresholds. In: Meersman, R., Dillon, T., Herrero, P. (eds.) OTM 2010. LNCS, vol. 6426, pp. 78–95. Springer, Heidelberg (2010). Scholar
  23. 23.
    Sánchez-González, L., García, F., Ruiz, F., Mendling, J.: Quality indicators for business process models from a gateway complexity perspective. Inf. Softw. Technol. 54(11), 1159–1174 (2012)CrossRefGoogle Scholar
  24. 24.
    Sánchez-GonzáLez, L., GarcíA, F., Ruiz, F., Piattini, M.: Toward a quality framework for business process models. Int. J. Coop. Inf. Syst. 22(01), 1350003 (2013)CrossRefGoogle Scholar
  25. 25.
    Sánchez-González, L., Ruiz, F., García, F., Cardoso, J.: Towards thresholds of control flow complexity measures for BPMN models. In: Proceedings of the 2011 ACM symposium on Applied computing, pp. 1445–1450. ACM (2011)Google Scholar
  26. 26.
    Schmidt, R., Nurcan, S.: Augmenting BPM with social software. In: Rinderle-Ma, S., Sadiq, S., Leymann, F. (eds.) BPM 2009. LNBIP, vol. 43, pp. 201–206. Springer, Heidelberg (2010). Scholar
  27. 27.
    Vanderfeesten, I., Cardoso, J., Mendling, J., Reijers, H.A., van der Aalst, W.M.: Quality metrics for business process models. BPM Workflow Handb. 144, 179–190 (2007)Google Scholar
  28. 28.
    Vanderfeesten, I., Reijers, H.A., Mendling, J., van der Aalst, W.M.P., Cardoso, J.: On a quest for good process models: the cross-connectivity metric. In: Bellahsène, Z., Léonard, M. (eds.) CAiSE 2008. LNCS, vol. 5074, pp. 480–494. Springer, Heidelberg (2008). Scholar
  29. 29.
    Vanderfeesten, I.T., Cardoso, J., Reijers, H.A.: A weighted coupling metric for business process models. In: CAiSE Forum, vol. 247 (2007)Google Scholar
  30. 30.
    Watahiki, K., Ishikawa, F., Hiraishi, K.: Formal verification of business processes with temporal and resource constraints. In: 2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC, pp. 1173–1180. IEEE (2011)Google Scholar
  31. 31.
    Weske, M.: Business Process Management: Concepts, Languages, Architectures. Springer, Heidelberg (2012). Scholar
  32. 32.
    Yahya, F., Boukadi, K., Ben-Abdallah, H., Maamar, Z.: A fuzzy logic-based approach for assessing the quality of business process models. In: Proceedings of the 12th International Conference on Software Technologies - Volume 1, ICSOFT, pp. 61–72. INSTICC, SciTePress (2017)Google Scholar
  33. 33.
    Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)CrossRefGoogle Scholar
  34. 34.
    Zadeh, L.A.: Is there a need for fuzzy logic? Inf. Sci. 178(13), 2751–2779 (2008)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Fadwa Yahya
    • 1
    Email author
  • Khouloud Boukadi
    • 1
  • Hanêne Ben-Abdallah
    • 2
  • Zakaria Maamar
    • 3
  1. 1.Sfax UniversitySfaxTunisia
  2. 2.King Abdulaziz UniversityJeddahKingdom of Saudi Arabia
  3. 3.Zayed UniversityDubaiUAE

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