Selection of software reliability model based on BP neural network

Authors:
Yingbo Wu;Xu Wang
Affiliations:
School of Software Engineering, Chongqing University, Chongqing, China;School of Mechanical Engineering, Chongqing University, Chongqing, China
Venue:
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
Year:
2011

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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.