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Statistical Inference on Software Reliability Assuming Exponential Fault Correction Time

Statistical Inference on Software Reliability Assuming Exponential Fault Correction Time Abstract Most of the software reliability models are based on reliability growth models which deal only with the fault detection process. In such models it is assumed that faults are corrected immediately after being detected or the time to correct a fault is not taken into account. This assumption may not be realistic in practice. In this paper we propose a software reliability model taking into account the fault correction time. The software failure times as well as correction times are assumed to be exponential. The model is formulated as an alternating renewal process. The properties of the reliability model are studied through the renewal process. The system parameters are estimated by means of the maximum likelihood estimators and the properties of the estimators are discussed. We also propose some large sample tests for the system parameters. Some numerical studies are made to evaluate the power of the tests. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Economic Quality Control de Gruyter

Statistical Inference on Software Reliability Assuming Exponential Fault Correction Time

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Publisher
de Gruyter
Copyright
Copyright © 2010 by the
ISSN
1869-6147
eISSN
1869-6147
DOI
10.1515/eqc.2010.019
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Abstract

Abstract Most of the software reliability models are based on reliability growth models which deal only with the fault detection process. In such models it is assumed that faults are corrected immediately after being detected or the time to correct a fault is not taken into account. This assumption may not be realistic in practice. In this paper we propose a software reliability model taking into account the fault correction time. The software failure times as well as correction times are assumed to be exponential. The model is formulated as an alternating renewal process. The properties of the reliability model are studied through the renewal process. The system parameters are estimated by means of the maximum likelihood estimators and the properties of the estimators are discussed. We also propose some large sample tests for the system parameters. Some numerical studies are made to evaluate the power of the tests.

Journal

Economic Quality Control – de Gruyter

Published: Dec 1, 2010

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