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WIREs Comp Stat

Software reliability

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In this article, we present an overview of the state of the art in software reliability. We present some of the traditional software reliability models as well as recent advances in modeling. In so doing, we discuss use of hidden Markov models, as well as nonparametric models including mixtures of Dirichlet processes. Furthermore, we review decision problems in software reliability such as testing strategies and optimal stopping rules. We discuss computational issues associated with use of the models, their statistical analyses and development of optimal strategies. WIREsComp Stat 2011 3 269–281 DOI: 10.1002/wics.159

Figure 1.

Musa's system 40 data.

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Figure 2.

Posterior distributions of λ15, λ45, λ85, and λ101.

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Figure 3.

Posterior distributions of λi's over different stages testing.

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Figure 4.

Posterior distribution of K.

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Figure 5.

The m‐stage decision tree for the optimal release problem.

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Browse by Topic

Computational Bayesian Methods > Bayesian Methods and Theory
Data Structures > Time Series, Stochastic Processes, and Functional Data
Statistical Methods > Reliability, Survivability, and Quality Control
Computer Science Models > Software/Statistical Software

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