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A sequential Bayesian generalization of the Jelinski–Moranda software reliability model
Author(s) -
Washburn Alan
Publication year - 2006
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.20148
Subject(s) - software quality , failure rate , computer science , reliability (semiconductor) , generalization , gamma distribution , reliability engineering , gamma process , sequence (biology) , software , fault (geology) , binomial distribution , bayesian probability , binomial (polynomial) , statistics , mathematics , artificial intelligence , software development , programming language , engineering , mathematical analysis , power (physics) , physics , quantum mechanics , seismology , biology , genetics , geology
The Jelinski–Moranda model of software reliability is generalized by introducing a negative‐binomial prior distribution for the number of faults remaining, together with a Gamma distribution for the rate at which each fault is exposed. This model is well suited to sequential use, where a sequence of reliability forecasts is made in the process of testing or using the software. We also investigate replacing the Gamma distribution with a worst‐case assumption about failure rates (the worst‐case failure rate in models such as this is not infinite, since faults with large failure rates are immediately discovered and removed). © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006
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