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View-Based Reverse Engineering Approach for Enhancing Model Interoperability and Reusability in Process-Driven SOAs

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High Confidence Software Reuse in Large Systems (ICSR 2008)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 5030))

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Abstract

In many companies, process-driven SOAs are introduced using technical process languages, such as BPEL, to orchestrate services. The process models developed using this approach are often too complex and hard to reuse because all process-related concerns are tangled in only one type of model. To make the models more understandable for non-technical stakeholders, many companies additionally introduce high-level process descriptions, e.g., specified in BPMN or EPCs, to offer a non-technical view of the processes. This divergence of process languages often leads to inconsistencies after a few evolution steps. We propose a novel approach based on architectural views that not only offers models tailored to the various stakeholders’ concerns but also provides an automated integration of models at different abstraction levels. In particular, we propose an extensible reverse-engineering tool-chain to automatically populate various view models with information from existing process descriptions and generate executable code from these view models.

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Authors and Affiliations

  1. Distributed Systems Group, Information Systems Institute, Vienna University of Technology, Austria

    Huy Tran, Uwe Zdun & Schahram Dustdar

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  1. Huy Tran
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  2. Uwe Zdun
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  3. Schahram Dustdar
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Hong Mei

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Tran, H., Zdun, U., Dustdar, S. (2008). View-Based Reverse Engineering Approach for Enhancing Model Interoperability and Reusability in Process-Driven SOAs. In: Mei, H. (eds) High Confidence Software Reuse in Large Systems. ICSR 2008. Lecture Notes in Computer Science, vol 5030. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68073-4_23

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  • DOI: https://doi.org/10.1007/978-3-540-68073-4_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68062-8

  • Online ISBN: 978-3-540-68073-4

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