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Research has yielded approaches for predicting future changes and defects in software artifacts, based on historical information, helping developers in effectively allocating their (limited) resources. Developers are unlikely able to focus on all predicted software artifacts, hence the ordering of predictions is important for choosing the right artifacts to concentrate on. We propose using a Genetic Algorithm (GA) for tailoring prediction models to prioritize classes with more changes/defects.doi:10.7287/peerj.preprints.1160v1 dblp:journals/peerjpre/AlexandruPPBG15 fatcat:uxqrhkp4zrgd7heb3od7bssbqy