DocumentCode
2847566
Title
Hybrid Bayesian Network Models for Predicting Software Reliability
Author
Blackburn, Mark ; Huddell, Benjamin
Author_Institution
Stevens Inst. of Technol., Hoboken, NJ, USA
fYear
2012
fDate
20-22 June 2012
Firstpage
33
Lastpage
34
Abstract
This paper discusses the results of applying a hybrid Bayesian Network to predict software reliability measures. The model combined quantitative testing data with subjective expert judgment about program-specific aspects over many releases. Six different programs were analyzed using historical data to validate the model. The model predictions varied from project-to-project suggesting that additional program variables should be included in the model.
Keywords
Bayes methods; program testing; software reliability; hybrid Bayesian network model; program-specific aspect; quantitative testing data; software reliability prediction; subjective expert judgment; Bayesian methods; Computational modeling; Data models; Predictive models; Software; Software reliability; Bayesian network models; quantitative and qualitative models; software reliability;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Security and Reliability Companion (SERE-C), 2012 IEEE Sixth International Conference on
Conference_Location
Gaithersburg, MD
Print_ISBN
978-1-4673-2670-4
Type
conf
DOI
10.1109/SERE-C.2012.38
Filename
6258443
Link To Document