Title :
Estimating the number of undetected errors: Bayesian model selection
Author :
Basu, Sanjib ; Ebrahimi, Nader
Author_Institution :
Div. of Stat., Northern Illinois Univ., DeKalb, IL, USA
Abstract :
Sometimes complex software systems fail because of faults introduced in the requirements and design stages of the development process. To improve the reliability of a software, several reviewers inspect documents related to requirements and design. Some faults are detected in this process but often a few remain undetected until the software is developed. Ebrahimi (1997) developed frequentist methods to estimate the number of faults which are nor discovered. Later, Basu and Ebrahimi and Basu developed different Bayesian models. These different Bayesian models yield different estimates of the number of undetected errors. It was further found that changes in the prior parameters often result in measurable changes in the estimates of undetected errors. The authors address the issue of model selection among these different models. They advocate two model selection methods. The first method uses marginal likelihood and Bayes factor whereas the second method is based on cross-validated likelihood. These methods are illustrated in the software review data of AT&T 5 ESS switches
Keywords :
Bayes methods; software reliability; system monitoring; AT&T 5 ESS switches; Bayes factor; Bayesian model selection; complex software systems; cross-validated likelihood; design stage; faults; marginal likelihood; model selection; requirements stage; software reliability; software review data; undetected error estimation; Application software; Bayesian methods; Computer errors; Electronic switching systems; Fault detection; Maximum likelihood estimation; Software systems; Statistics; Switches; Yield estimation;
Conference_Titel :
Software Reliability Engineering, 1998. Proceedings. The Ninth International Symposium on
Conference_Location :
Paderborn
Print_ISBN :
0-8186-8991-9
DOI :
10.1109/ISSRE.1998.730765