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An Automatic Architecture Reconstruction and Refactoring Framework

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Software Engineering Research,Management and Applications 2011

Part of the book series: Studies in Computational Intelligence ((SCI,volume 377))

Abstract

A variety of sources have noted that a substantial proportion of non trivial software systems fail due to unhindered architectural erosion. This design deterioration leads to low maintainability, poor testability and reduced development speed. The erosion of software systems is often caused by inadequate understanding, documentation and maintenance of the desired implementation architecture. If the desired architecture is lost or the deterioration is advanced, the reconstruction of the desired architecture and the realignment of this desired architecture with the physical architecture both require substantial manual analysis and implementation effort. This paper describes the initial development of a framework for automatic software architecture reconstruction and source code migration. This framework offers the potential to reconstruct the conceptual architecture of software systems and to automatically migrate the physical architecture of a software system toward a conceptual architecture model. The approach is implemented within a proof of concept prototype which is able to analyze java system and reconstruct a conceptual architecture for these systems as well as to refactor the system towards a conceptual architecture.

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Author information

Authors and Affiliations

  1. SERL, Auckland University of Technology, Private Bag 92006, Auckland, 1142, New Zealand

    Frederik Schmidt, Stephen G. MacDonell & Andrew M. Connor

Authors
  1. Frederik Schmidt
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  2. Stephen G. MacDonell
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  3. Andrew M. Connor
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Editors and Affiliations

  1. Computer Science Department, Software Engineering & Information Technology Institute, Central Michigan University, 48859, Mt. Pleasant, MI, USA

    Roger Lee

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Schmidt, F., MacDonell, S.G., Connor, A.M. (2012). An Automatic Architecture Reconstruction and Refactoring Framework. In: Lee, R. (eds) Software Engineering Research,Management and Applications 2011. Studies in Computational Intelligence, vol 377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23202-2_7

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  • DOI: https://doi.org/10.1007/978-3-642-23202-2_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23201-5

  • Online ISBN: 978-3-642-23202-2

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