Research of Software Defect Prediction Based on Complex Network

In order to predict software defects, this paper proposes a software defect prediction method based on complex network analysis. Most of the existing evaluation methods are based on undirected, unweighted network, failing to reflect the real situation of complex software. First, method proposed in this paper abstracts software system as directed weighted network on the granularity of class. Then, based on PageRank algorithm, this paper proposes KeyNodeRank algorithm to calculate node importance in global network. Node importance can be used to predict defects of software system. Experimental results show that the proposed method has a higher accuracy in predicting software defect. It has important significance for locating software defects, testing, improving software quality and software maintenance.