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Pareto optimal search based refactoring at the design level
Pareto optimal search based refactoring at the design level   (Citations: 27)
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Refactoring aims to improve the quality of a software sys- tems' structure, which tends to degrade as the system evolves. While manually determining useful refactorings can be chal- lenging, search based techniques can automatically discover useful refactorings. Current search based refactoring ap- proaches require metrics to be combined in a complex fash- ion, and produce a single sequence of refactorings. In this paper we show how Pareto optimality can improve search based refactoring, making the combination of metrics easier, and aiding the presentation of multiple sequences of optimal refactorings to users.
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