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Abstract

This paper describes a numerical method for optimising the conservative confidence bound on the reliability of a system based on statistical testing of its individual components. It provides an alternative to the sub-optimal test plan algorithms identified by the authors in an earlier research paper. For a given maximum number of component tests, this numerical method can derive an optimal test plan for any arbitrary system structure.

The optimisation method is based on linear programming which is more efficient than the alternative integer programming approach. In addition, the optimisation process need only be performed once for any given system structure as the solution can be re-used to compute an optimal integer test plan for a different maximum number of component tests. This approach might have broader application to other optimisation problems.

Publication Type:	Conference or Workshop Item (Paper)
Additional Information:	This version of the contribution has been accepted for publication, after peer review but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-14835-4_24. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms
Publisher Keywords:	Statistical testing, Confidence bounds, Software reliability, Fault tolerance, Linear programming
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Departments:	School of Science & Technology School of Science & Technology > Computer Science School of Science & Technology > Computer Science > Software Reliability
SWORD Depositor:	Symplectic Administrator

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