Optimal Stopping Rules for Software Testing

Nilgun Morali, Refik Soyer
Aegean University, The George Washington University

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.


Bayesian inference, dynamic programming, kalman filter, preposterior analysis, software reliability


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