Selection of Software Reliability Model Based on BP Neural Network

被引：0

作者：

Wu, Yingbo ^{[1
]}

Wang, Xu ^{[2
]}

机构：

[1] Chongqing Univ, Sch Software Engn, Chongqing 400044, Peoples R China

[2] Chongqing Univ, Sch Mech Engn, Chongqing 400044, Peoples R China

来源：

ADVANCES IN SWARM INTELLIGENCE, PT I | 2011年 / 6728卷

关键词：

software reliability model; BP neural network; model selection; PREDICTION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：489 / 496

页数：8

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