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Generalized partition testing via Bayes linear methods

Coolen, F.P.A.; Goldstein, M.; Munro, M.

Authors

F.P.A. Coolen

M. Munro



Abstract

This paper explores the use of Bayes linear methods related to partition testing for software. If a partition of the input domain has been defined, the method works without the assumption of homogeneous (revealing) subdomains, and also includes the possibility to learn, from testing inputs in one subdomain, about inputs in other subdomains, through explicit definition of the correlations involved. To enable practical application, an exchangeability structure needs to be defined carefully, for which means the judgements of experts with relation to the software is needed. Next to presenting the basic idea of Bayes linear methods and how it can be used to generalize partition testing, some important aspects related to applications as well as for future research are discussed.

Citation

Coolen, F., Goldstein, M., & Munro, M. (2001). Generalized partition testing via Bayes linear methods. Information and Software Technology, 43(13), 783-793. https://doi.org/10.1016/s0950-5849%2801%2900185-9

Journal Article Type Article
Online Publication Date Nov 1, 2001
Publication Date Nov 1, 2001
Deposit Date Aug 24, 2006
Journal Information and Software Technology
Print ISSN 0950-5849
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 43
Issue 13
Pages 783-793
DOI https://doi.org/10.1016/s0950-5849%2801%2900185-9
Keywords Bayes linear methods, Expert knowledge, Partition testing, Software testing theory.

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