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DEFECT DETECTION USING SELF-ORGANIZING MAPS

This paper addresses the problem of software defect detection, an important problem which helps to improve the software systems’ maintainability and evolution. In order to detect defective entities within a software system, a self-organizing feature map is proposed. The trained map will be able to identify, using unsupervised learning, if a software module is defective or not. We experimentally evaluate our approach on three open-source case studies, also providing a comparison with similar existing approaches. The obtained results emphasize the effectiveness of using self-organizing maps for software defect detection and confirm the potential of our proposal.