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A Rating Tool for the Automated Selection of Software Refactorings that Remove Antipatterns to Improve Performance and Stability

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Software Technologies (ICSOFT 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1077))

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Abstract

Antipatterns are known to be bad solutions for recurring design problems. To detect and remove antipatterns has proven to be a useful mean to improve the quality of software. While there exist several approaches to detect antipatterns automatically, existing work on antipattern detection often does not solve the detected design problems automatically. Although there exist refactorings that have the potential to significantly increase the quality of a program, it is hard to decide which refactorings effectively yield improvements with respect to performance and stability. In this paper, we present a rating tool that makes use of static antipattern detection together with software profiling for the automated selection of refactorings that remove antipatterns and are promising candidates to improve performance and stability. Our key idea is to extend a previously proposed heuristics that utilizes software properties determined by both static code analyses and dynamic software analyses to compile a list of concrete refactorings sorted by their assessed potential to improve performance with an approach to identify refactorings that may improve stability. We do not impose an order on the refactorings that may improve stability. We demonstrate the practical applicability of our overall approach with experimental results.

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Author information

Authors and Affiliations

  1. QMETHODS – Business & IT Consulting GmbH, Berlin, Germany

    Nikolai Moesus & Matthias Scholze

  2. Software and Embedded Systems Engineering, Technische Universität Berlin, Berlin, Germany

    Sebastian Schlesinger

  3. Embedded Systems Group, University of Münster, Münster, Germany

    Paula Herber

Authors
  1. Nikolai Moesus
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  2. Matthias Scholze
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  3. Sebastian Schlesinger
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  4. Paula Herber
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Corresponding author

Correspondence to Paula Herber .

Editor information

Editors and Affiliations

  1. Information Systems Group, University of Twente, Enschede, The Netherlands

    Marten van Sinderen

  2. Wrocław University of Economics, Wrocław, Poland

    Leszek A. Maciaszek

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Moesus, N., Scholze, M., Schlesinger, S., Herber, P. (2019). A Rating Tool for the Automated Selection of Software Refactorings that Remove Antipatterns to Improve Performance and Stability. In: van Sinderen, M., Maciaszek, L. (eds) Software Technologies. ICSOFT 2018. Communications in Computer and Information Science, vol 1077. Springer, Cham. https://doi.org/10.1007/978-3-030-29157-0_2

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  • DOI: https://doi.org/10.1007/978-3-030-29157-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-29156-3

  • Online ISBN: 978-3-030-29157-0

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