Optimal Stopping Rules for Software Testing
Nov 30 1993
In this paper we address the problem of determining when to terminate the testing/modification process and release a piece of software during the software development. We present a Bayesian decision theoretic approach by formulating the software release problem as a sequential decision problem. By using a non-Gaussian Kalman filter type of model, proposed by Chen and Singpurwalla (1994) to track software reliability, we are able to obtain tractable expressions for inference and determine a one-stage look ahead optimal stopping rule under a specific class of loss functions.
Keywords:Bayesian inference, dynamic programming, kalman filter, preposterior analysis, software reliability