Filtering clones for individual user based on machine learning analysis
Jiachen Yang, Keisuke Hotta, Yoshiki Higo, Hiroshi Igaki, Shinji Kusumoto · 2012
Results from code clone detectors may contain plentiful useless code clones, and judging whether a code clone is useful varies from user to user based on different purposes of them. We are planing a system to study the judgment of each individual user by applying machine learning algorithms on code clones. We describe the reason why individual judgment should be respected and how in this paper.