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GECCO
2005
Springer

Hybridizing evolutionary algorithms and clustering algorithms to find source-code clones

13 years 9 months ago
Hybridizing evolutionary algorithms and clustering algorithms to find source-code clones
This paper presents a hybrid approach to detect source-code clones that combines evolutionary algorithms and clustering. A case-study is conducted on a small C++ code base. The preliminary investigation indicates that such an approach is effective in detecting groups of source-code clones. Categories and Subject Descriptors D.2.7 [Software Engineering]: Restructuring, reverse engineering, and reengineering, I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search. General Terms Algorithms, Design, Experimentation. Keywords Evolutionary Algorithms, Software Engineering, Clone Detection.
Andrew Sutton, Huzefa H. Kagdi, Jonathan I. Maleti
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where GECCO
Authors Andrew Sutton, Huzefa H. Kagdi, Jonathan I. Maletic, L. Gwenn Volkert
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