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Towards a mutation-based automatic framework for evaluating code clone detection tools
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Source C3S2E; Vol. 290 archive
Proceedings of the 2008 C3S2E conference table of contents
Montreal, Quebec, Canada
POSTER SESSION: Posters table of contents
Pages 137-140  
Year of Publication: 2008
ISBN:978-1-60558-101-9
Authors
Chanchal K. Roy  Queen's University, Kingston, ON, Canada
James R. Cordy  Queen's University, Kingston, ON, Canada
Sponsors
: ACM International Conference Proceedings Series
Concordia University : Concordia University
: BytePress
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 5,   Downloads (12 Months): 43,   Citation Count: 1
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ABSTRACT

In the last decade, a great many code clone detection tools have been proposed. Such a large number of tools calls for a quantitative comparison, and there have been several attempts to empirically evaluate and compare many of the state-of-the-art tools. However, a recent study shows that there are several factors that could influence the the validity of the results of such comparisons. In order to overcome the effects of such factors (at least in part), in this student poster paper we outline a mutation-based controlled frame-work for evaluating clone detection tools using edit-based mutation operators that model cloning actions. While the framework is not yet completely implemented and as yet we do not have experimental data, we anticipate that such a framework will provide a useful contribution to the community by providing a more solid objective foundation for tool evaluation.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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C. K. Roy and J. R. Cordy. A Survey on Software Clone Detection Research. School of Computing TR 2007-541, Queen's University, 115 pp., 2007.
 
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C. K. Roy and J. R. Cordy. Scenario-Based Comparison of Clone Detection Techniques. In ICPC, 10 pp., 2008 (to appear).
 
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C. K. Roy and J. R. Cordy. NICAD: Accurate Detection of Near-Miss Intentional Clones Using Flexible Pretty-Printing and Code Normalization. In ICPC, 10 pp., 2008 (to appear).
 
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F. V. Rysselberghe and S. Demeyer. Evaluating Clone Detection Techniques. In ELISA, 12pp., 2003.


Collaborative Colleagues:
Chanchal K. Roy: colleagues
James R. Cordy: colleagues