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.WIREsComp Stat2011 3 269–281 DOI: 10.1002/wics.159This article is categorized under:Statistical and Graphical Methods of Data Analysis > Bayesian Methods and TheoryStatistical and Graphical Methods of Data Analysis > Reliability, Survivability, and Quality ControlSoftware for Computational Statistics > Software/Statistical SoftwareData: Types and Structure > Time Series, Stochastic Processes, and Functional Data