Business & Information Systems Engineering

, Volume 58, Issue 1, pp 7–17 | Cite as

Criteria and Heuristics for Business Process Model Decomposition

Review and Comparative Evaluation
  • Fredrik MilaniEmail author
  • Marlon Dumas
  • Raimundas Matulevičius
  • Naved Ahmed
  • Silva Kasela
Research Paper


It is generally agreed that large process models should be decomposed into sub-processes in order to enhance understandability and maintainability. Accordingly, a number of process decomposition criteria and heuristics have been proposed in the literature. This paper presents a review of the field revealing distinct classes of criteria and heuristics. The study raises the question of how different decomposition heuristics affect process model understandability and maintainability. To address this question, an experiment is conducted where two different heuristics, one based on breakpoints and the other on data objects, were used to decompose a flat process model. The results of the experiment show that, although there are minor differences, the heuristics cause very similar results in regard to understandability and maintainability as measured by various process model metrics.


Process modeling Decomposition Process model metrics 



This research was supported by the European Social Fund via the Doctoral Studies and Internationalisation Programme – DoRa.


  1. Antón A, McCracken W, Potts C (1994) Goal decomposition and scenario analysis in business process reengineering. Adv Inform Syst LNCS 811:94–104Google Scholar
  2. Becker J, Becker J, Winkelmann A (2009) Developing a business process modeling language for the banking sector – a design science approach. In: Proceedings AMCIS 2009. Accessed 18 Oct 2015
  3. Braunnagel D, Johannsen F, Leist S (2014) Coupling and process modeling – an analysis at hand of the eEPC. In: Proceedings Modellierung 2014. Wien, pp 121–136. Accessed 18 Oct 2015
  4. Burton-Jones A, Meso PN (2004) Conceptualizing systems for understanding: an empirical test of decomposition principles in object oriented analysis. Inf Syst Res 17(1):38–60CrossRefGoogle Scholar
  5. Cardoso J (2005) How to measure the control-flow complexity of web process and workflows. Accessed 18 Oct 2015
  6. Cardoso J, Mendling J (2006) A discourse on complexity of process models. Bus Process Manag Workshops LNCS 4103:117–128CrossRefGoogle Scholar
  7. Conforti R, Dumas M, García-Bañuelos L, La Rosa M (2014) Beyond tasks and gateways: discovering BPMN models with subprocesses, boundary events and activity markers. Bus Process Manag LNCS 8659:101–117Google Scholar
  8. Daneva M, Heib R, Scheer A (1996) Benchmarking business process models. Technical Report, Saarland UniversityGoogle Scholar
  9. Davis R (2001) Business process modelling with ARIS: a practical guide. Springer, New YorkCrossRefGoogle Scholar
  10. De Leoni M, Munoz-Gama J, Carmona J, Van der Aalst WMP (2014) Decomposing alignment-based conformance checking of data-aware process models. In: On the move to meaningful internet systems: OTM 2014 Conferences. Springer, Heidelberg, pp 3–20Google Scholar
  11. Dijkman R, Gfeller B, Küster J, Völzer H (2011) Identifying refactoring opportunities in process model repositories. Inf Softw Technol 53(9):937–948CrossRefGoogle Scholar
  12. Dijkman R, Vanderfeesten I, Reijers HA (2014) Business process architectures: overview, comparison and framework. Enterp Inf Syst. doi: 10.1080/17517575.2014.928951 Google Scholar
  13. Dumas M, La Rosa M, Mendling J, Raul M (2012) Understanding business process models: the costs and benefits of structuredness. In: CAiSE’12 Proc 24th Int Conf Adv Inf Syst Eng, vol 7328, pp 31–46Google Scholar
  14. Eberle H, Unger T, Leymann F (2009) Process fragments. In: On the move to meaningful internet systems. LNCS, vol 5870, pp 398–405Google Scholar
  15. Eppinger SD, Whintey DE, Smith RP, Gebala DA (1994) A model-based method for organizing task in product development. Res Eng Des 6(1):1–13CrossRefGoogle Scholar
  16. Huang Y, He K, Feng Z, Huang Y (2014) Business process consolidation based on E-RPSTs. In: Serv. (SERVICES), 2014 IEEE World Congr. IEEE, pp 354–361Google Scholar
  17. Ivanović D, Carro M, Hermenegildo M (2010) Automatic fragment identification in workflows based on sharing analysis. LNCS 6470:350–364Google Scholar
  18. Johannsen F, Leist S (2012) Wand and Weber’s decomposition model in the context of business process modeling. Bus Inf Syst Eng 4(5):275–286CrossRefGoogle Scholar
  19. Khalaf R, Leymann F (2006) E role-based decomposition of business processes using BPEL. In: Proceeding ICWS’06 Proc IEEE Int Conf Web Serv, pp 770–780Google Scholar
  20. Kim K, Won J, Kim C (2005) A fragment-driven process modeling methodology. In: Computational science and its applications – ICCSA 2005. LNCS, vol 3482, pp 817–826Google Scholar
  21. Kitchenham B (2004) Procedures for performing systematic reviews. Technical Report, Keele Univ, vol 33, p 28Google Scholar
  22. Kock NFJ, McQueen RJ (1996) Product flow, breadth and complexity of business processes: an empirical study of 15 business processes in three organizations. Bus Process Re-eng Manag J 2(2):8–22CrossRefGoogle Scholar
  23. Kueng P, Kawalek P (1997) Goal-based business process models: creation and evaluation. Bus Process Manag J 3:17–38CrossRefGoogle Scholar
  24. Kusiak A, Wang J (1993) Efficient organizing of design activities. Int J Prod Res 31(4):753–769CrossRefGoogle Scholar
  25. Latva-Koivisto A (2001) Finding a complexity measure for business process models. Tech. Rep. Helsinki Univ. Technol. Syst. Anal., pp 1–26Google Scholar
  26. León HCM, Farris JA, Letens G, Hernandez A (2013) An analytical management framework for new product development processes featuring uncertain iterations. J Eng Technol Manag 30(1):45–71CrossRefGoogle Scholar
  27. Li W, Moon YB (2012) Modeling and managing engineering changes in a complex product development process. Int J Adv Manuf Technol 63(9):863–874CrossRefGoogle Scholar
  28. Malinova M, Leopold H, Mendling J (2013) An empirical investigation on the design of process architectures. In: Proceedings of the 11th international conference on Wirtschaftsinformatik 2013, LeipzigGoogle Scholar
  29. Malone TW, Crowston K, Lee JLJ, Pentland B (1993) Tools for inventing organizations: toward a handbook of organizational processes. Proc Second Work Enabling Technol Collab Enterp 45:425–443Google Scholar
  30. Mendling J (2006) Testing density as a complexity metric for EPCs. Tech. Rep. Vienna Univ. Econ. Bus. Adm.Google Scholar
  31. Mendling J, Neumann G, van der Aalst W (2007) Understanding the occurrence of errors in process models based on metrics. Lect Notes Comput Sci 4803:113–130CrossRefGoogle Scholar
  32. Mendling J, Reijers HA, van der Aalst WMP (2010) Seven process modeling guidelines (7PMG). Inf Softw Technol 52(2):127–136CrossRefGoogle Scholar
  33. Milani F, Dumas M, Matulevičius R (2013) Decomposition driven consolidation of process models. Adv Inform Syst Eng LNCS 7908:193–207Google Scholar
  34. Muehlen MZ, Wisnosky D, Kindrick J (2010) Primitives: design guidelines and architecture for BPMN models. In: Australas. Conf. Inf. SystGoogle Scholar
  35. Muketha G, Ghani A (2010) A survey of business processes complexity metrics. Inf Technol J 9(7):1336–1344CrossRefGoogle Scholar
  36. Pimmler TU, Eppinger SD (1994) Integration analysis of product decompositions. Alfred P. Sloan School of Management, MIT, CambridgeGoogle Scholar
  37. Pohl K (2010) Requirements engineering: fundamentals, principles, and techniques. Springer, New YorkCrossRefGoogle Scholar
  38. Polyvyanyy A, Smirnov S, Weske M (2009) The triconnected abstraction of process models. In: Dayal U, Eder J, Koehler J, Reijers H (eds) Business process management, vol 5701. LNCS, pp 229–244Google Scholar
  39. Polyvyanyy A, Smirnov S, Weske M (2010) Business process model abstraction. In: Handb. Bus. Process Manag. 1. Springer, Heidelberg, pp 149–166Google Scholar
  40. Reijers HA (2003) A cohesion metric for the definition of activities in a workflow process. In: Proc. EMMSAD. pp 116–125Google Scholar
  41. Reijers HA, Mendling J (2011) A study into the factors that influence the understandability of business process models. IEEE Trans Syst Man Cybern 41(3):449–462CrossRefGoogle Scholar
  42. Reijers HA, Vanderfeesten I (2004) Cohesion and coupling metrics for workflow process design. In: Proc Bus Process Manag – Second Int Conf BPM 2004, Potsdam, pp 290–305Google Scholar
  43. Reijers HA, Mendling J, Dijkman RM (2011) Human and automatic modularizations of process models to enhance their comprehension. Inf Syst 36(5):881–897CrossRefGoogle Scholar
  44. Rogers JL (1990) Knowledge-based tool for decomposing complex design problems. J Comput Civ Eng 4(4):298–312CrossRefGoogle Scholar
  45. Rosa L, Mendling J, La Rosa M (2012) Thresholds for error probability measures of business process models. J Syst Softw 85(5):1188–1197CrossRefGoogle Scholar
  46. Sadiq S, Governatori G (2010) Managing regulatory compliance in business processes. In: vom Brocke J, Rosemann M (eds) Handb. Bus. Process Manag. 2. Springer, Heidelberg, pp 159–175Google Scholar
  47. Sharp A, McDermott P (2009) Workflow modeling: tools for process improvement and applications development. Artech HouseGoogle Scholar
  48. Smirnov S, Dijkman R, Mendling J, Weske M (2010) Meronymy-based aggregation of activities in business process models. Concept Model LNCS 6412:1–14Google Scholar
  49. Smirnov S, Reijers HA, Weske M, Nugteren T (2012) Business process model abstraction: a definition, catalog, and survey. Distrib Parallel Databases 30(1):63–99CrossRefGoogle Scholar
  50. Smith RP, Morrow J (1999) Product development process modeling. Des Stud 20(3):237–261CrossRefGoogle Scholar
  51. Turetken O, Demirors O (2011) Plural: a decentralized business process modeling method. Inf Manag 48(6):235–247CrossRefGoogle Scholar
  52. Uba R, Dumas M, García-Bañuelos L, La Rosa M (2011) Clone detection in repositories of business process models. Bus Process Manag LNCS 6896:248–264Google Scholar
  53. Vanderfeesten I, Cardoso J, Reijers HA (2007) A weighted coupling metric for business process models. CEUR Workshop Proc 247:41–44Google Scholar
  54. Vanderfeesten I, Reijers HA, Mendling J, van der Aalst WMP, Cardoso J (2008a) On a quest for good process models: the cross-connectivity metric. LNCS 5074:480–494Google Scholar
  55. Vanderfeesten I, Reijers HA, van der Aalst WMP (2008b) Evaluating workflow process designs using cohesion and coupling metrics. Comput Ind 59(5):420–437CrossRefGoogle Scholar
  56. Vanhatalo J, Völzer H, Koehler J (2009) The refined process structure tree. Data Knowl Eng 68(9):793–818. doi: 10.1016/j.datak.2009.02.015 CrossRefGoogle Scholar
  57. Weber B, Reichert M, Mendling J, Reijers HA (2011) Refactoring large process model repositories. Comput Ind 62(5):467–486CrossRefGoogle Scholar
  58. Westerberg AW, Subrahmainan E, Reich Y, Konda S (1997) Designing the process design process. Comput Chem Eng 21(Supplement):S1–S9CrossRefGoogle Scholar
  59. Wolter C, Schaad A (2007) Modeling of task-based authorization constraints in BPMN. In: Alonso G, Dadam P, Rosemann M (eds) Business process management, vol 4714. LNCS, pp 64–79Google Scholar

Copyright information

© Springer Fachmedien Wiesbaden 2015

Authors and Affiliations

  • Fredrik Milani
    • 1
    Email author
  • Marlon Dumas
    • 1
  • Raimundas Matulevičius
    • 1
  • Naved Ahmed
    • 1
  • Silva Kasela
    • 1
  1. 1.University of TartuTartuEstonia

Personalised recommendations