关键词: 经验软件工程, 软件缺陷预测, 实证研究

Abstract: Software defect prediction (SDP) plays an important role in improving software quality and customers’ satisfaction, reducing developing costs and controlling risks. On the one hand, many theoretical and empirical studies on software defect prediction have been carried out in academic community; but on the other hand, the industry has found that applications of SDP have some shortcomings, such as poor practicability, low efficiency and failing to consider the severity of defects. In order to find out the specific reasons, firstly static software defect prediction is divided into defect-proneness prediction, defect number/distribution density prediction and defect module ranking prediction according to different prediction targets. Then, the existing research work and problems of the above three types of static software defect prediction are summarized from four aspects, namely the selection of software metrics, the evaluation data repository, the construction of defect prediction model and the evaluation of defect prediction model. Particularly, the constructions of defect-proneness and defect module ranking prediction models are emphatically summarized. Finally, the challenges and bottlenecks faced by static software defect prediction are pointed out based on the application in industry, and further research directions are prospected.

Key words: empirical software engineering, software defect prediction, empirical studies