Prediction of Business Process Model Quality Based on Structural Metrics

  • Laura Sánchez-González
  • Félix García
  • Jan Mendling
  • Francisco Ruiz
  • Mario Piattini
Conference paper

DOI: 10.1007/978-3-642-16373-9_35

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6412)
Cite this paper as:
Sánchez-González L., García F., Mendling J., Ruiz F., Piattini M. (2010) Prediction of Business Process Model Quality Based on Structural Metrics. In: Parsons J., Saeki M., Shoval P., Woo C., Wand Y. (eds) Conceptual Modeling – ER 2010. ER 2010. Lecture Notes in Computer Science, vol 6412. Springer, Berlin, Heidelberg

Abstract

The quality of business process models is an increasing concern as enterprise-wide modelling initiatives have to rely heavily on non-expert modellers. Quality in this context can be directly related to the actual usage of these process models, in particular to their understandability and modifiability. Since these attributes of a model can only be assessed a posteriori, it is of central importance for quality management to identify significant predictors for them. A variety of structural metrics have recently been proposed, which are tailored to approximate these usage characteristics. In this paper, we address a gap in terms of validation for metrics regarding understandability and modifiability. Our results demonstrate the predictive power of these metrics. These findings have strong implications for the design of modelling guidelines.

Keywords

Business process measurement correlation analysis regression analysis BPMN 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Laura Sánchez-González
    • 1
  • Félix García
    • 1
  • Jan Mendling
    • 2
  • Francisco Ruiz
    • 1
  • Mario Piattini
    • 1
  1. 1.Alarcos Research Group, TSI DepartmentUniversity of Castilla La ManchaCiudad RealSpain
  2. 2.Humboldt-Universität zu BerlinBerlinGermany

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