Optimal Stopping Rules for Software Testing

Authors: 
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.

Keywords: 

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

Manuscript: 

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