Quasi-Bayesian software reliability model with small samples

• Published in: Journal of Shanghai University Vol. 13; no. 4; pp. 301 - 304
• Main Author: 张金 涂俊翔 陈卓宁 严晓光
• Format: Journal Article
• Language: English
• Published: Heidelberg Shanghai University Press 01.08.2009; School of Mechanical Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,P.R.China; Kaimu Information Technology Ltd.,Wuhan 430223,P.R.China%School of Mechanical Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,P.R.China
• Subjects: Classical Mechanics; Engineering; Environment; Life Sciences; Materials Science; Mathematical and Computational Engineering; Mechatronics; Mechatronics Engineering; 不确定性; 专家判断; 小样本; 概率分布; 模型集成; 统计数据; 贝叶斯; 软件可靠性模型; imprecise probability; quasi-Bayesian analysis; software reliability model; expert judgment
• ISSN: 1007-6417; 1863-236X
• DOI: 10.1007/s11741-009-0410-1

In traditional Bayesian software reliability models, it was assume that all probabilities are precise. In practical applications the parameters of the probability distributions are often under uncertainty due to strong dependence on subjective information of experts＇ judgments on sparse statistical data. In this paper, a quasi-Bayesian software reliability model using interval-valued probabilities to clearly quantify experts＇ prior beliefs on possible intervals of the parameters of the probability distributions is presented. The model integrates experts＇ judgments with statistical data to obtain more convincible assessments of software reliability with small samples. For some actual data sets, the presented model yields better predictions than the Jelinski-Moranda （JM） model using maximum likelihood （ML）.