Using Bayesian statistics to support testing of software systems

F. P. A. Coolen, M Goldstein and D. A. Wooff

Journal of Risk and Reliability, 2007, vol. 221, issue 1, 85-93

Abstract: Testing of software systems is crucial for reliability, but is often difficult owing to the many uncertainties and practical constraints involved. The nature of the software development process often prevents straightforward application of standard statistical methods. In recent years, the current authors have developed a Bayesian statistical approach to support software testers, in particular for high reliability testing of software systems near the end of the development process. Throughout this period, they have been collaborating with an industrial partner to ensure practical relevance of the methods. An important difference when compared with existing methods to support software testing is that the judgements and current practice of the software testers are central, so the method helps testers to structure their judgements and optimize corresponding test actions, the latter process being far too complex to be done effectively without the support of such sophisticated statistical methods. In the present paper, an overview is given of this approach and of results to date. Recent progress is also discussed, together with related future research topics aimed at wide practical applicability of the approach.

Keywords: expert judgement; high reliability; reliability test planning; software reliability; test selection (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1243/1748006XJRR2 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:221:y:2007:i:1:p:85-93

DOI: 10.1243/1748006XJRR2

Access Statistics for this article

More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().