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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2015: Artificial Intelligence and Soft Computing pp 649–659Cite as

Measuring Complexity of Business Process Models Integrated with Rules

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9120))

Abstract

Complexity assessment is often used in software and knowledge engineering for controlling the quality and improving models. In fact, complexity is one of the main factors affecting the understability and maintainability of models. Although there are many complexity measures that can be used in order to assess the complexity of process models or rule bases, the complexity of the integrated model of processes with rules is not addressed and constitutes a challenging issue. In this paper, we consider a new metric that is suitable for measuring the integrated models and present a short evaluation based on the selected cases of different size.

The paper is a part of the PhD thesis of the author [1]. The research presented in the paper was supported by the HiBuProBuRul Project funded from NCN (National Science Centre) resources for science (no. DEC-2011/03/N/ST6/00909).

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Author information

Authors and Affiliations

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

    Krzysztof Kluza

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  1. Krzysztof Kluza
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Correspondence to Krzysztof Kluza .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Czestochowa, Poland

    Leszek Rutkowski

  2. Czestochowa University of Technology, Czestochowa, Poland

    Marcin Korytkowski

  3. Czestochova Univ of Technology, Częstochova, Poland

    Rafal Scherer

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

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. Louisville, Kentucky, USA

    Jacek M. Zurada

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Kluza, K. (2015). Measuring Complexity of Business Process Models Integrated with Rules. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9120. Springer, Cham. https://doi.org/10.1007/978-3-319-19369-4_57

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  • DOI: https://doi.org/10.1007/978-3-319-19369-4_57

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19368-7

  • Online ISBN: 978-3-319-19369-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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