Software reliability prediction based on ensemble models

Abstract

Software reliability is the determinant factor of software reliability prediction and software quality estimation during software testing period. This report offers an ensemble technique model of different artificial neural networks for forecasting of software reliability. The experimental results of the proposed model are compared with other states of the traditional models and it is noted that the proposed architectural model outperforms its competent models. The proposed architectural ensemble model has been adequately tested on three benchmark datasets and its results tested with an artificial neural network approach and a mathematical linear model. The experimental result demonstrates that the ensemble model yields better performance than other models.