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Searching for Configurations in Clone Evaluation – A Replication Study

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Search Based Software Engineering (SSBSE 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9962))

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Abstract

Clone detection is the process of finding duplicated code within a software code base in an automated manner. It is useful in several areas of software development such as code quality analysis, bug detection, and program understanding. We replicate a study of a genetic-algorithm based framework that optimises parameters for clone agreement (EvaClone). We apply the framework to 14 releases of Mockito, a Java mocking framework. We observe that the optimised parameters outperform the tools’ default parameters in term of clone agreement by 19.91 % to 66.43 %. However, the framework gives undesirable results in term of clone quality. EvaClone either maximises or minimises a number of clones in order to achieve the highest agreement resulting in more false positives or false negatives introduced consequently.

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Notes

  1. 1.

    The full set of optimised parameters are at cragkhit.github.io/ssbsechallenge2016.

References

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Author information

Authors and Affiliations

  1. University College London, London, UK

    Chaiyong Ragkhitwetsagul, Matheus Paixao, Manal Adham, Saheed Busari & Jens Krinke

  2. Queen Mary University of London, London, UK

    John H. Drake

Authors
  1. Chaiyong Ragkhitwetsagul
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  2. Matheus Paixao
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  3. Manal Adham
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  4. Saheed Busari
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  5. Jens Krinke
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  6. John H. Drake
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Corresponding author

Correspondence to Chaiyong Ragkhitwetsagul .

Editor information

Editors and Affiliations

  1. University College London, London, United Kingdom

    Federica Sarro

  2. Michigan State University , East Lansing, Michigan, USA

    Kalyanmoy Deb

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© 2016 Springer International Publishing AG

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Ragkhitwetsagul, C., Paixao, M., Adham, M., Busari, S., Krinke, J., Drake, J.H. (2016). Searching for Configurations in Clone Evaluation – A Replication Study. In: Sarro, F., Deb, K. (eds) Search Based Software Engineering. SSBSE 2016. Lecture Notes in Computer Science(), vol 9962. Springer, Cham. https://doi.org/10.1007/978-3-319-47106-8_20

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  • DOI: https://doi.org/10.1007/978-3-319-47106-8_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47105-1

  • Online ISBN: 978-3-319-47106-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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