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Bootstrapping confidence in future safety based on past safe operation

Bishop, P. ORCID: 0000-0003-3307-5159, Povyakalo, A. ORCID: 0000-0002-4068-422X & Strigini, L. ORCID: 0000-0002-4246-2866 (2022). Bootstrapping confidence in future safety based on past safe operation. Paper presented at the 2022 IEEE 33rd International Symposium on Software Reliability Engineering (ISSRE 2022), 31 Oct - 3 Nov 2022, Charlotte, NC, USA.

Abstract

We propose an approach to managing the rolling out of a new system type so as to contain the risk of mishaps in its operation to an acceptable level, while using the evidence of safe operation to support confidence for extending the scale of operation. This cautious approach of “bootstrapping” confidence in the safety of a system is now widely applied to autonomous vehicle (AVs), our example. AVs are subject to extreme safety requirements; a major concern is the inability to give meaningful quantitative assurance of safety of an AV type, to the extent required by society, before it is used extensively. We exploit a previously published approach to achieving more moderate, but useful, assurance, e.g. about low enough probability of causing accidents in a limited period of operation; and demonstrate how this approach supports choice of production/deployment strategies, so as to manage the growth of a fleet of AVs for a given accepted level of risk. Via a formal mathematical description of “confidence bootstrapping”, we show: (1) that it is a substantially sound approach in the right circumstances, and useful for deciding about the early deployment phase for a new system; (2) how much confidence can be rightly derived from such a “cautious deployment” approach, avoiding over-optimism; (3) under which conditions our sound formulas for future confidence are applicable; (4) thus, which analyses of the concrete situations, and/or constraints on practice, are needed in order to enjoy the advantages of provably correct confidence in adequate future safety over a definite time (“confidence horizon”).

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
Subjects: Q Science > QA Mathematics > QA76 Computer software
Departments: School of Science & Technology > Computer Science
School of Science & Technology > Computer Science > Software Reliability
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