Sequential procedure for Software Reliability estimation

We use a sequential method to allocate software test cases among partitions of a software to minimize the expected loss incurred by the Bayes estimator of the overall software reliability. The Bayesian approach allows us to take advantage of the previous information obtained from testing. We will show that the myopic sampling scheme has advantages over the optimal fixed in terms of the expected loss incurred when the overall reliability is estimated by its Bayes estimator. Theoretical results and numerical are provided for the comparison. This myopic scheme shows a great promise in software reliability estimation.