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Conservative bounds for the pfd of a 1-out-of-2 software-based system based on an assessor’s subjective probability of “not worse than independence”

Littlewood, B. & Povyakalo, A. A. (2013). Conservative bounds for the pfd of a 1-out-of-2 software-based system based on an assessor’s subjective probability of “not worse than independence”. IEEE Transactions on Software Engineering, 39(12), pp. 1641-1653. doi: 10.1109/TSE.2013.31

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Abstract

We consider the problem of assessing the reliability of a 1-out-of-2 software-based system, in which failures of the two channels cannot be assumed to be independent with certainty. An informal approach to this problem assesses the channel pfds (probabilities of failure on demand) conservatively and then multiplies these together in the hope that the conservatism will be sufficient to overcome any possible dependence between the channel failures. Our intention here is to place this kind of reasoning on a formal footing. We introduce a notion of “not worse than independence” and assume that an assessor has a prior belief about this, expressed as a probability. We obtain a conservative prior system pfd, and show how a conservative posterior system pfd can be obtained following the observation of a number of demands without system failure. We present some illustrative numerical examples, discuss some of the difficulties involved in this way of reasoning, and suggest some avenues of future research.

Publication Type: Article
Additional Information: © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Publisher Keywords: System reliability; Software fault tolerance; 1-out-of-2 system; Dependent failures; Subjective probability
Subjects: Q Science > QA Mathematics > QA76 Computer software
Departments: School of Science & Technology > Computer Science > Software Reliability
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