Bayesian optimum stopping rule for software release
This Paper proposes a Bayesian approach to find out the optimum stopping rule of software testing. We consider a discrete periodic debugging framework so that software can be released for market once the criteria are fulfilled. Simplification of stopping rules were obtained by using some specific prior distributions of the number of remaining bugs. We also develop necessary and sufficient conditions for stopping the software testing. Some illustrative examples are presented.
Chakraborty, Ashis Kumar; Basak, Gopal Krishna; and Das, Suchismita, "Bayesian optimum stopping rule for software release" (2019). Journal Articles. 920.