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Automated Consistency Management in BPMN Based Business Process Models

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Intelligent Technologies and Applications (INTAP 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 932))

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Abstract

The main aim of this paper is emphasis on how to incorporate changes in existing BPMN based business process models considering the correctness and consistency. However, modifications and alterations in existing BPMN models are only time consuming but also error-prone. First, we take a BPMN model as an input and create its XML file. Then, an XML parser is used to parse the xml file and extract the BPMN and UML class elements which will further be verified. Proposed approach will overcome all the inconsistencies in case of modification within existing BPMN models which can enhance the effectiveness of any business process models. Business process exist in a business organization. Bank, open bank account, cheque cash, check balance at ATM, etc. Customer requirements vary with respect of time, then we have to update and improve, refine business processes. The frequent changes in business processes may make them inconsistent with respect to other business process. Such inconsistencies create problems in business activities. It is difficult to identify such inconsistencies manually due to involvement of lot of effort and time. There should be an automated approach or an automated tool that can help in identifying the possible inconsistencies in business processes after changes.

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Correspondence to Mamoona Ishaq .

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Ishaq, M., Choudhary, M.A. (2019). Automated Consistency Management in BPMN Based Business Process Models. In: Bajwa, I., Kamareddine, F., Costa, A. (eds) Intelligent Technologies and Applications. INTAP 2018. Communications in Computer and Information Science, vol 932. Springer, Singapore. https://doi.org/10.1007/978-981-13-6052-7_25

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  • DOI: https://doi.org/10.1007/978-981-13-6052-7_25

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6051-0

  • Online ISBN: 978-981-13-6052-7

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