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Optimal stopping in software testing
Author(s) -
Morali Nilgun,
Soyer Refik
Publication year - 2003
Publication title -
naval research logistics (nrl)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 68
eISSN - 1520-6750
pISSN - 0894-069X
DOI - 10.1002/nav.10048
Subject(s) - computer science , sequential analysis , inference , software , bayesian probability , optimal stopping , mathematical optimization , bayesian inference , reliability (semiconductor) , artificial intelligence , mathematics , statistics , quantum mechanics , programming language , power (physics) , physics
In this paper we address the problem of how to decide when to terminate the testing/modification process and to release the software during the development phase. We present a Bayesian decision theoretic approach by formulating the optimal release problem as a sequential decision problem. By using a non‐Gaussian Kalman filter type model, proposed by Chen and Singpurwalla (1994), to track software reliability, we are able to obtain tractable expressions for inference and determine a one‐stage look ahead stopping rule under reasonable conditions and a class of loss functions. © 2002 Wiley Periodicals, Inc. Naval Research Logistics, 2003
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