Research of Software Defect Prediction Based on CART

Abstract

Through the software defect prediction can effectively guide the rational distribution of software system development resources, so as to improve the quality of software and software reliability. In order to fully utilize the existing historical data to guide the software development of existing software system development, this paper based on an improved classification and regression tree (Classification and Regression, CART) algorithm software defect prediction models. The paper first principal component analysis of the data predicted correlation dimension (Principle Component Analysis, PCA) between data and reduce the data, and configured according to the theory and optimized CART decision tree algorithm, existing software defect prediction system, and with traditional defect prediction method, the experimental results show that the proposed prediction model has higher prediction accuracy and stability.