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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao zbMATH Openarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Article
Data sources: zbMATH Open
International Statistical Review
Article . 1994 . Peer-reviewed
Data sources: Crossref
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Software Reliability Modeling

Software reliability modeling
Authors: Singpurwalla, Nozer D.; Wilson, Simon P.;

Software Reliability Modeling

Abstract

Summary: Probability models and statistical methods are a popular technique for evaluating the reliability of computer software. This paper reviews the literature concerning these methods, with an emphasis on the historical perspective. The use of stochastic techniques is justified, and the various probability models that have been proposed, along with any associated statistical estimation and inference procedure, are described. Examples of the models applied to real software failure data are given. A classic software development problem -- how long software should be tested before it is released into the marketplace -- is analyzed from a decision theoretic standpoint. Finally, the direction of future research is contemplated.

Keywords

Reliability and life testing, historical perspective, review, de-eutrophication, real software failure data, Theory of software, utility, non-homogeneous Poisson process, mean value function, decision theory, autoregressive process, maximum likelihood, failure rate

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
69
Top 10%
Top 10%
Top 10%
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