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Bayesian graphical models for high complexity testing : aspects of implementation.

Wooff, D.A. and Goldstein, M. and Coolen, F.P.A. (2018) 'Bayesian graphical models for high complexity testing : aspects of implementation.', in Analytic methods in systems and software testing. Hoboken, NJ, USA: Wiley, pp. 213-243.

Abstract

This chapter presents a brief review of the Bayesian graphical models (BGM) approach to software testing, which the authors developed in close collaboration with industrial software testers. It provides discussion of a range of topics for practical implementation of the BGM approach, including modeling for test–retest scenarios, the expected duration of the retest cycle, incorporation of multiple failure modes, and diagnostic methods. The chapter addresses model maintenance and evolution, including consideration of novel system functionality. It discusses end‐to‐end testing of complex systems, and presents methods to assess the viability of the BGM approach for individual applications. These are all important aspects of high‐complexity testing which software testers have to deal with in practice, and for which Bayesian statistical methods can provide useful tools. The chapter also provides the basic approaches to these important issues. These should enable software testers, with support from statisticians, to develop implementations for specific test scenarios.

Item Type:Book chapter
Full text:Publisher-imposed embargo
(AM) Accepted Manuscript
File format - PDF
(263Kb)
Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1002/9781119357056.ch8
Date accepted:No date available
Date deposited:25 July 2018
Date of first online publication:06 July 2018
Date first made open access:No date available

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