Titlebook: Statistical Methods in Software Engineering; Reliability and Risk Nozer D. Singpurwalla,Simon P. Wilson Book 1999 Springer Science+Business

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The Optimal Testing and Release of Software,dictions about failure times. In Chapter 5 we have seen how probability models can be used to predict productivity, and how the calculus of probability can be used for the classification of software development houses. However, the quantification of uncertainty, inferences from failure data, and the

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Foundational Issues: Probability and Reliability,ole of a reference time τ at which probabilities were assessed was mentioned, and finally, it was argued that for any random quantity ε, a subjective interpretation of its probability .(ε | .) was an appropriate paradigm for dealing with the kind of problems that we are involved with here.

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Models for Measuring Software Reliability,ecent developments in the overall enterprise of model development. The issue of how to use these models in applications involves the topic of statistical inference, and this has been delegated to Chapter 4.

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Statistical Analysis of Software Failure Data,s a way of simplifying the probability specification process. The parameters being unobservable, our uncertainty about them was described by a prior distribution. The prior distribution is specific to an individual and may vary from individual to individual.

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The Optimal Testing and Release of Software,on theory has a natural place in software engineering, and indeed in the general area of design, engineering, and manufacturing [cf. Singpurwalla (1992), (1993), and (1998c)]. The purpose of this chapter is to give an overview of the key elements of decision theory, and to describe how this theory c

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Other Developments: Open Problems,de a bird’s-eye view of some of these topics, and to put forth some open problems that they pose. It is hoped that this will inspire other researchers to pursue each topic in more detail than what we report. With this in mind, we have selected three topics for further discussion: dynamic modeling an