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In the existing studies on software prediction, the most proposed methods are usually assessed over the public datasets like NASA metrics data repository, which include a combination of code metrics merely. Obviously, the process metric is also one of the key factors that affect the defect-proneness of software modules. In this paper, life-cycle based management process metrics set and history change...
In the case of metrics-based software defect prediction, an intelligent selection of metrics is one of the key factors that affect the model performance. To solve the problem that only the correlation between software metrics is considered and the issue of redundance is tend to be ignored in the current studies, a new algorithm which combines ReliefF feature selection algorithm and correlation analysis...
In the case of metrics-based software defect prediction, an intelligent selection of metrics plays an important role in improving the model performance. In this paper, we use different ways for feature selection and dimensionality reduction to determine the most important software metrics. Three different classifiers are utilized, namely Naïve Bayes, support vector machine and decision tree. On the...
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