We present a novel approach to detect refactoring opportunities by measuring the participation of references between types in instances of patterns representing design flaws. This technique is validated using an experiment where we analyse a set of 95 open-source Java programs for instances of four patterns representing modularisation problems. It turns out that our algorithm can detect high impact refactorings opportunities - a small number of references such that the removal of those references removes the majority of patterns from the program.
@article{arxiv.1006.1747,
title = {On the Detection of High-Impact Refactoring Opportunities in Programs},
author = {Jens Dietrich and Catherine McCartin and Ewan Tempero and Syed M. Ali Shah},
journal= {arXiv preprint arXiv:1006.1747},
year = {2011}
}
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