Study on Optimization of Software Regressive Testing Based on RBF Neural Networks

Abstract

In order to reduce times of software regression testing, a new research idea and method is proposed based on RBFN (Radial Basis Function Network). Using the adaptive ability of network study, regression testing is optimized by its learning strategy. The simulation results demonstrate the new method can forecast regressive testing effectively, and implement very little error. It means an important meaning for developing new effective method of soft testing in the future.