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Managing the uncertainties of software testing: a Bayesian approach
Author(s) -
Rees Kearton,
Coolen Frank,
Goldstein Michael,
Wooff David
Publication year - 2001
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.411
Subject(s) - computer science , software quality , software , software reliability testing , reliability engineering , bayesian probability , risk based testing , process (computing) , reliability (semiconductor) , test strategy , quality (philosophy) , regression testing , model based testing , system integration testing , verification and validation , software engineering , software construction , software development , test case , machine learning , artificial intelligence , engineering , power (physics) , philosophy , physics , operating system , operations management , epistemology , quantum mechanics , regression analysis , programming language
Testing of software systems involves many complex problems for test managers. Important issues to be considered include how to quantify reliability, how to design tests, which tests should be performed given time, cost and resource constraints, what are the implications of test failures, what tests should be re‐run following corrections to rectify faults, and so forth. All of these issues are related to the uncertainties involved in the quality of the software and the process of testing. In a continuing collaboration, the use of Bayesian graphical models has been explored to model these uncertainties and to support software testers and test managers with their complex tasks. This paper discusses some features of Bayesian graphical models which are pertinent to modelling software testing problems, and in particular the kind of support they can provide to test managers and the use of such models in a practical environment. Details of the modelling process are presented elsewhere. Copyright © 2001 John Wiley & Sons, Ltd.