Software & Systems Modeling

, Volume 18, Issue 2, pp 1079–1095 | Cite as

Theoretical foundations and implementation of business process diagrams’ complexity management technique based on highlights

  • Gregor JoštEmail author
  • Marjan Heričko
  • Gregor Polančič
Special Section Paper


The main purpose of business process diagrams is to make the communication between process-related stakeholders more effective. To this end, they need to be simple to read, which is often challenging to achieve. In this manner, the complexity of business process diagrams can negatively affect their correctness and understandability. The goal of this paper was to investigate an approach that makes business process diagrams appear less complex, without changing the corresponding notation. This was done by manipulating one of the properties of the notation’s elements, namely opacity. Firstly, a literature overview was performed in order to obtain the theoretical foundations. Secondly, an exploratory case study was conducted and the results were applied in practice. Finally, the proposed solution was implemented in the form of a prototype software solution. Our analysis demonstrated that the structural complexity of the diagrams decreases when applying the proposed solution.


Business process diagram Complexity Highlights Opacity BPMN 


  1. 1.
    Moody, D.: The ‘physics’ of notations: toward a scientific basis for constructing visual notations in software engineering. IEEE Trans. Softw. Eng. 35(6), 756–779 (2009)CrossRefGoogle Scholar
  2. 2.
    Gruhn, V., Laue, R.: Complexity metrics for business process models. In: 9th International Conference on Business Information Systems, BIS 2006, pp. 1–12 (2006)Google Scholar
  3. 3.
    Latva-Koivisto, A.M.: Finding a complexity measure for business process models, Research report Helsinki University of Technology, Systems Analysis Laboratory (2001)Google Scholar
  4. 4.
    Decker, G., Puhlmann, F.: Extending BPMN for modeling complex choreographies. In: Proceedings of the On the Move to Meaningful Internet Systems 2007: CoopIS, DOA, ODBASE, GADA, and IS: OTM Confederated International Conferences CoopIS, DOA, ODBASE, GADA, and IS 2007, Vilamoura, Portugal, November 25–30, 2007, Part I, pp. 24–40 (2007)Google Scholar
  5. 5.
    Fernández, H.F., Palacios-González, E., García-Díaz, V., PelayoG-Bustelo, B.C., Sanjuán Martínez, O., Cueva Lovelle, J.M.: SBPMN—an easier business process modeling notation for business users. Comput. Stand. Interfaces 32(1–2), 18–28 (2010)CrossRefGoogle Scholar
  6. 6.
    zur Muehlen, M., Recker, J.: How much language is enough? Theoretical and practical use of the business process modeling notation. In: Advanced Information Systems Engineering 20th International Conference, CAiSE 2008 Montpellier, France, June 16–20, 2008 Proceedings, pp. 465–479 (2008)Google Scholar
  7. 7.
    Dumas, M., La Rosa, M., Mendling, J., Reijers, H.A.: Fundamentals of business process management. Springer, Berlin (2013)CrossRefGoogle Scholar
  8. 8.
    Mili, H., Tremblay, G., Jaoude, G.B., Lefebvre, E., Elabed, L., El Boussaidi, G.: Business process modeling languages: sorting through the alphabet soup. ACM Comput. Surv. 43(1), 1–56 (2010)CrossRefGoogle Scholar
  9. 9.
    Chinosi, M., Trombetta, A.: BPMN: an introduction to the standard. Comput. Stand. Interfaces 34(1), 124–134 (2012)CrossRefGoogle Scholar
  10. 10.
    Tran, H., Zdun, U., Dustdar, S.: View-based integration of process-driven SOA models at various abstraction levels. In: Kutsche, R-D., Milanovic, N. (eds.) Model-Based Software and Data Integration, pp. 55–66. Springer, Berlin (2008)Google Scholar
  11. 11.
    Kocbek, M., Jost, G., Hericko, M., Polancic, G.: Business process model and notation: the current state of affairs. Comput. Sci. Inf. Syst. 12(2), 509–539 (2015)CrossRefGoogle Scholar
  12. 12.
    Harmon, P., Wolf, C.: Business process modeling survey. In: Business process trends, p. 36 (2011).
  13. 13.
    Rosemann, M.: Potential pitfalls of process modeling: part B. Bus. Process Manag. J. 12(3), 377–384 (2006)CrossRefGoogle Scholar
  14. 14.
    Terry, M., Mynatt, E.D.: Enhancing general-purpose tools with multi-state previewing capabilities. Knowl. Based Syst. 18(8), 415–425 (2005)CrossRefGoogle Scholar
  15. 15.
    Cardoso, J.: How to measure the control-flow complexity of web process and workflows. Workflow Handb. 2005, 199–212 (2005)Google Scholar
  16. 16.
    Edmonds, B.: Complexity and scientific modelling. Found. Sci. 5(3), 379–390 (2000)MathSciNetCrossRefzbMATHGoogle Scholar
  17. 17.
    La Rosa, M., ter Hofstede, A.H.M., Wohed, P., Reijers, H.A., Mendling, J., van der Aalst, W.M.P.: Managing process model complexity via concrete syntax modifications. IEEE Trans. Ind. Inform. 7(2), 255–265 (2011)CrossRefGoogle Scholar
  18. 18.
    Moody, D.: Complexity effects on end user understanding of data models: an experimental comparison of large data model representation methods. In: Proceedings of the Tenth European Conference on Information Systems (ECIS’2002), pp. 482–496 (2002)Google Scholar
  19. 19.
    Reijers, H.A., Freytag, T., Mendling, J., Eckleder, A.: Syntax highlighting in business process models. Decis. Support Syst. 51(3), 339–349 (2011)CrossRefGoogle Scholar
  20. 20.
    Müller, R., Rogge-Solti, A.: BPMN for healthcare processes. In: 3nd Central-European Workshop on Services and Their Composition ZEUS 2011, vol. 705, pp. 65–72 (2011)Google Scholar
  21. 21.
    Moody, D.: What makes a good diagram? Improving the cognitive effectiveness of diagrams in IS development. In: Wojtkowski, W., Wojtkowski, W.G., ZupanÄiÄ, J., Magyar, G., Knapp, G. (eds.) Advances in Information Systems Development: New Methods and Practice for the Networked Society, pp. 481–492. Springer, Boston (2007)Google Scholar
  22. 22.
    Petrusel, R., Mendling, J., Reijers, H.A.: How visual cognition influences process model comprehension. Decis. Support Syst. 96, 1–16 (2017)CrossRefGoogle Scholar
  23. 23.
    Petrusel, R., Mendling, J.: Eye-tracking the factors of process model comprehension tasks. In: Salinesi, C., Norrie, M.C., Pastor, Ó. (eds.) Advanced Information Systems Engineering: Proceedings of the 25th International Conference, CAiSE 2013, Valencia, Spain, June 17–21, 2013, pp. 224–239. Springer, Berlin (2013)Google Scholar
  24. 24.
    Erol, S.: Coloring Support for Process Diagrams: A Review of Color Theory and a Prototypical Implementation. Vienna University of Economics and Business, Wien (2015)Google Scholar
  25. 25.
    Glassner, A.: Interpreting alpha. J. Comput. Graph. Tech. JCGT 4(2), 30–44 (2015)Google Scholar
  26. 26.
    León, K., Mery, D., Pedreschi, F., León, J.: Color measurement in L*a*b* units from RGB digital images. Food Res. Int. 39(10), 1084–1091 (2006)CrossRefGoogle Scholar
  27. 27.
    Park, S., Pantanowitz, L., Parwani, A.V.: Digital imaging in pathology. Clin. Lab. Med. 32(4), 557–584 (2012)CrossRefGoogle Scholar
  28. 28.
    ITS Project Methodology (Process Improvement Interview Questions): [Online]. (2010). Accessed 03 Dec 2016
  29. 29.
    Gagne, D., Trudel, A.: Time-BPMN. In: 2009 IEEE Conference on Commerce and Enterprise Computing, pp. 361–367 (2009)Google Scholar
  30. 30.
    Khlif, W., Zaaboub, N., Ben-Abdallah, H.: Coupling metrics for business process modeling. WSEAS Trans. Comput. 9(1), 31–41 (2010)Google Scholar
  31. 31.
    Lerner, B.S., Christov, S., Osterweil, L.J., Bendraou, R., Kannengiesser, U., Wise, A.: Exception handling patterns for process modeling. IEEE Trans. Softw. Eng. 36(2), 162–183 (2010)CrossRefGoogle Scholar
  32. 32.
    O. M. G. D. Number, P. D. F. A. File, BPMN 2.0 by Example. Group, vol. 0, p. 47 (2010)Google Scholar
  33. 33.
    Rolón, E., Sánchez, L., García, F., Ruiz, F., Piattini, M., Caivano, D., Visaggio, G.: Prediction models for BPMN usability and maintainability. In: 2009 IEEE Conference on Commerce and Enterprise Computing, pp. 383–390 (2009)Google Scholar
  34. 34.
    Reynoso, L., Rolón, E., Genero, M., García, F., Ruiz, F., Piattini, M.: Formal definition of measures for BPMN models. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5891, pp. 285–306. LNCS (2009)Google Scholar
  35. 35.
    Moody, D.L., Heymans, P., Matulevičius, R.: Visual syntax does matter: improving the cognitive effectiveness of the i* visual notation. Requir. Eng. 15(2), 141–175 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Gregor Jošt
    • 1
    Email author
  • Marjan Heričko
    • 1
  • Gregor Polančič
    • 1
  1. 1.Faculty of Electrical Engineering and Computer ScienceUniversity of MariborMariborSlovenia

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