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Conservative Confidence Bounds in Safety, from Generalised Claims of Improvement & Statistical Evidence

Salako, K. ORCID: 0000-0003-0394-7833, Strigini, L. ORCID: 0000-0002-4246-2866 and Zhao, X. (2021). Conservative Confidence Bounds in Safety, from Generalised Claims of Improvement & Statistical Evidence. Paper presented at the The 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 21-24 Jun 2021, Taipei, Taiwan.

Abstract

“Proven-in-use”, “globally-at-least-equivalent”, “stress-tested”, are concepts that come up in diverse contexts in acceptance, certification or licensing of critical systems. Their common feature is that dependability claims for a system in a certain operational environment are supported, in part, by evidence – viz of successful operation – concerning different, though related, system[s] and/or environment[s], together with an auxiliary argument that the target system/environment offers the same, or improved, safety. We propose a formal probabilistic (Bayesian) organisation for these arguments. Through specific examples of evidence for the “improvement” argument above, we demonstrate scenarios in which formalising such arguments substantially increases confidence in the target system, and show why this is not always the case. Example scenarios concern vehicles and nuclear plants. Besides supporting stronger claims, the mathematical formalisation imposes precise statements of the bases for “improvement” claims: seemingly similar forms of prior beliefs are sometimes revealed to imply substantial differences in the claims they can support.

Publication Type: Conference or Workshop Item (Paper)
Publisher Keywords: Reliability claims, statistical testing, safetycritical systems, ultra-high reliability, conservative Bayesian inference, field testing, not worse than existing systems, software re-use, globally at least equivalent, proven in use
Subjects: H Social Sciences > HA Statistics
Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
School of Mathematics, Computer Science & Engineering > Computer Science > Software Reliability
Date available in CRO: 12 May 2021 10:58
Date deposited: 12 May 2021
Date of acceptance: 8 March 2021
URI: https://openaccess.city.ac.uk/id/eprint/26128
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