关键词: 神经网络模型, 神经网络集成模型, 故障预测

Abstract: Fault prediction in software system is a key process in reliability prediction during the software testing phase. Using the forward and current correlative information of faults during the testing process to predict the fault information in afterward testing phase, it can contribute to guide the test and rationally allocate the testing resource. The fault time series known in the forward software testing process is used to model the fault predictive models by means of Non-Homogeneous Poisson Process（NHPP）, neural networks（NN）, neural network ensembles, et al. By modeling three different examples with the mean relative error of 3.02%, 5.88% and 6.58% in G-O model while 0.19%, 1.88% and 1.455% in neural network ensemble model, the result shows that neural network ensemble model has more predictive ability.

Key words: neural networks model, neural network ensembles model, fault prediction