An efficient test allocation for software reliability estimation

We propose an efficient sampling scheme in the software reliability estimation. In contrast to fixed sampling schemes, where the proportion of test cases taken from each partition is determined before reliability testing begins, we make allocation decisions dynamically throughout the testing process. We then refine these estimates in an iterative manner as we sample. We also compare the result from the accelerated sampling scheme with the best fixed sampling scheme and demonstrate its superiority over the best fixed sampling scheme in terms of the expected loss incurred when the overall reliability is estimated by its Bayes estimator both theoretically and through Monte Carlo simulations.