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Square Complexity Metrics for Business Process Models

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Advances in Business ICT

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 257))

Abstract

Complexity metrics for Business Process (BP) are used for the better understanding, and controlling quality of the models, thus improving their quality. In the paper we give an overview of the existing metrics for describing various aspects of BP models. We argue, that the design process of BP models can be improved by the availability of metrics that are transparent and easy to be interpreted by the designers. Therefore, we propose simple yet practical square metrics for describing complexity of a BP model based on the Durfee and Perfect square concept. These metrics are easy to interpret and provide basic information about the structural complexity of themodel. The proposed metrics are to be used with models built with Business Process Model and Notation (BPMN), which is currently the most widespread language used for BP modeling. Moreover, we present a set of BPMN models analyzed with our metrics. Finally, we introduce a tool implementing the discussed metrics. We compare the results to other important metrics, emphasizing the qualities of our approach.

The paper is supported by the AGH UST 11.11.120.859.

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Authors and Affiliations

  1. AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059, Krakow, Poland

    Krzysztof Kluza, Grzegorz J. Nalepa & Janusz Lisiecki

Authors
  1. Krzysztof Kluza
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  2. Grzegorz J. Nalepa
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  3. Janusz Lisiecki
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Correspondence to Krzysztof Kluza .

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Editors and Affiliations

  1. University of Economics in Katowice, Katowice, Poland

    Maria Mach-Król

  2. AGH University of Science and Technology, Krakow, Poland

    Tomasz Pełech-Pilichowski

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Kluza, K., Nalepa, G.J., Lisiecki, J. (2014). Square Complexity Metrics for Business Process Models. In: Mach-Król, M., Pełech-Pilichowski, T. (eds) Advances in Business ICT. Advances in Intelligent Systems and Computing, vol 257. Springer, Cham. https://doi.org/10.1007/978-3-319-03677-9_6

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  • DOI: https://doi.org/10.1007/978-3-319-03677-9_6

  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-03677-9

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