Prediction of the Software Security Defects Based on the Complex Network

Abstract

The traditional software defects prediction methods just evaluate the software defects based the unweighted undirected network, which do not reflect the real complex software system. Therefore, this paper proposes a software security defects prediction method based on the complex network. This method improves the PageRank algorithm and develops a KeyNodeRank algorithm based on the complex network. In this method, the software system is divided into different classes and these classes constitute a weighted directed network. In addition, the KeyNodeRank algorithm evaluates and ranks the importance of class nodes in the global network. In order to examine the validity of the software defects prediction method, this paper carries out an experiment. It is found that this method not only is accurate to predict and locate software defects and but also is very significant for improving software quality and maintaining software.