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DECISIVE: Designing Critical Systems With Iterative Automated Safety Analysis

Wei, R, Jiang, Z, Guo, X, Yang, R, Mei, H, Zolotas, A and Kelly, T (2023) DECISIVE: Designing Critical Systems With Iterative Automated Safety Analysis. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. p. 1. ISSN 0278-0070

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Abstract

Systems safety is becoming increasingly challenging due to the presence of ever-more complex applications. Safety analysis is an important aspect of Safety-Critical Systems Engineering (SCSE) to discover problems in system design that can potentially lead to hazards with risks that may lead to accidents. Performing safety analysis requires significant manual effort — its automation has become the research focus in the critical system domain due to the increasing complexity of systems and the emergence of open adaptive systems. In this paper, we propose a novel methodology in which automated safety analysis drives the design of safety-critical systems. We delve into the specifics of our approach and the supporting tools. Additionally, we discuss the method to integrate our approach into the current practice of SCSE. The experimental results reveal that the proposed approach with its supporting tool promotes the efficiency of safety analysis significantly, whilst maintaining high degrees of correctness, coverage and scalability.

Item Type: Article
Additional Information: This article has been accepted for publication in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/tcad.2023.3340596
Uncontrolled Keywords: 0906 Electrical and Electronic Engineering; 1006 Computer Hardware; Computer Hardware & Architecture
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Computer Science & Mathematics
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
SWORD Depositor: A Symplectic
Date Deposited: 11 Dec 2023 12:08
Last Modified: 11 Dec 2023 15:37
DOI or ID number: 10.1109/tcad.2023.3340596
URI: https://researchonline.ljmu.ac.uk/id/eprint/22067
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