Successive sampling and software reliability

Successive Sampling and Software Reliability

Estimating Software Reliability Using Inverse Sampling

|This paper addresses one of the perpetual questions faced by software developers, \How much testing is enough testing?". Software testing accounts for a substantial portion of software development costs, but releasing software with unacceptable reliability is also very costly. We begin with a discussion of how classical notions of reliability can be applied to deterministic software and explai...

Inference in Successive Sampling Discovery

A variety of practical problems of nite population inference can be addressed in the framework of successive sampling discovery models { population units are assumed drawn from a superpopulation distribution and then successively sampled according to a speciied`size-biased' selection mechanism. Formal statistical analysis of discovery data under such models is technically challenging, as exempl...

Quantile Estimation in Successive Sampling

In successive sampling on two occasions the problem of estimating a finite population quantile has been considered. The theory developed aims at providing the optimum estimates by combining (i) three double sampling estimators viz. ratio-type, product-type and regression-type, from the matched portion of the sample and (ii) a simple quantile based on a random sample from the unmatched portion o...

On Successive Sampling and Fixed Inclusion Probabilities

In the method of successive sampling, a sample of n distinct units is drawn from a population of N units one at a time. Each unit i is drawn with a fixed selection probability pi and any repeated units are ignored. When the pi are proportional to a given size measure, this is called probability proportional to size without replacement (PPSWOR). The first order inclusion probabilities πi of each...