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Application of Fuzzy Logic to Assess the Quality of BPMN Models

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Software Technologies (ICSOFT 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 868))

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Abstract

Modeling is the first stage in a Business Process’s (BP) lifecycle. A high-quality BP model is vital to the successful implementation, execution, and monitoring stages. Different works have evaluated BP models from a quality perspective. These works either used formal verification or a set of quality metrics. This paper adopts quality metric and targets models represented in Business Process Modeling and Notation (BPMN). It proposes an approach based on fuzzy logic along with a tool system developed under eclipse framework. The preliminary experimental evaluation of the proposed system shows encouraging results.

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Notes

  1. 1.

    https://sites.google.com/site/bposcteam2015/ressources.

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Author information

Authors and Affiliations

  1. Sfax University, Sfax, Tunisia

    Fadwa Yahya & Khouloud Boukadi

  2. King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

    Hanêne Ben-Abdallah

  3. Zayed University, Dubai, UAE

    Zakaria Maamar

Authors
  1. Fadwa Yahya
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  2. Khouloud Boukadi
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  3. Hanêne Ben-Abdallah
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  4. Zakaria Maamar
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Corresponding author

Correspondence to Fadwa Yahya .

Editor information

Editors and Affiliations

  1. King Juan Carlos University, Madrid, Spain

    Enrique Cabello

  2. University of Coimbra, Coimbra, Portugal

    Jorge Cardoso

  3. Wroclaw University of Economics, Wroclaw, Poland

    Leszek A. Maciaszek

  4. Computer Science, University of Twente, Enschede, The Netherlands

    Marten van Sinderen

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Yahya, F., Boukadi, K., Ben-Abdallah, H., Maamar, Z. (2018). Application of Fuzzy Logic to Assess the Quality of BPMN Models. In: Cabello, E., Cardoso, J., Maciaszek, L., van Sinderen, M. (eds) Software Technologies. ICSOFT 2017. Communications in Computer and Information Science, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-319-93641-3_9

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  • DOI: https://doi.org/10.1007/978-3-319-93641-3_9

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  • Online ISBN: 978-3-319-93641-3

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