关键词: 软件质量, 互信息, 属性选择, 最优属性子集, 缺陷预测

Abstract: Predicting defect-prone software modules accurately and effectively is an important way to control the quality of a software system during software development. Feature selection can highly improve the accuracy and efficiency of the software defect prediction model. A mutual information-based feature selection method for software defect prediction is proposed. The optimal feature subsets generated by the proposed approach were applied to train and test various prediction models. The experiment results show that all the classifiers achieve higher accuracy and performance by using the feature subset provided by proposed approach.

Key words: Software quality, Mutual information, Feature selection, Optimal feature subset, Defect prediction