Software Defect Prediction based on Machine Learning Algorithms

Software defect prediction is very important in software engineering. It uses the defects found in historical software modules to predict defects in new software modules, and provides decision support for planning and process management in software project. Machine learning is one of the core research directions in the field of artificial intelligence and covers many disciplines. In the research of software defect prediction, various machine learning methods have been widely studied and applied, and have been verified to obtain good performance. In this paper, the basic framework of software defect prediction model based on machine learning is described, several important prediction models are studied and discussed. Finally, the main problems of software defect prediction are summarized, and corresponding solutions are proposed.