Adaptive Genetic Algorithm Based Artificial Neural Network for Software Defect Prediction

Abstract

To meet the requirement of an efficient software defect prediction in this paper an evolutionary computing based neural network learning scheme has been developed that alleviates the existing Artificial Neural Network ANN limitations such as local minima and convergence issues To achieve optimal software defect prediction in this paper Adaptive-Genetic Algorithm A-GA based ANN learning and weightestimation scheme has been developed Unlike conventional GA in this paper we have used adaptive crossover and mutation probability parameter that alleviates the issue of disruption towards optimal solution We have used object oriented software metrics CK metrics for fault prediction and the proposed Evolutionary Computing Based Hybrid Neural Network HENN algorithm has been examined for performance in terms of accuracy precision recall F-measure completeness etc where it has performed better as compared to major existing schemes The proposed scheme exhibited 97 99 prediction accuracy while ensuring optimal precision Fmeasure and recall