Selection of software reliability model based on BP neural network

Abstract

Software reliability models are used for the estimation and prediction of software reliability. In a situation where reliability data is lacking and numerous models are available, the key to quantitative analysis of software reliability lies in the selection of an optimal model. This paper describes a model selection method which involves an encoding scheme with multiple evaluation metrics and uses back-propagation (BP) neural network to perform clustering algorithm. Finally, by utilizing 20 sets of failure data that are collected in actual software development projects, a simulation experiment is made. The result shows the method is both correct and feasible. © 2011 Springer-Verlag.