Abstract
AbstractIn 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. WIREs Comp Stat 2011 3 269–281 DOI: 10.1002/wics.159This article is categorized under: Statistical and Graphical Methods of Data Analysis > Bayesian Methods and Theory Statistical and Graphical Methods of Data Analysis > Reliability, Survivability, and Quality Control Software for Computational Statistics > Software/Statistical Software Data: Types and Structure > Time Series, Stochastic Processes, and Functional Data
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