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Safety Case Templates for Autonomous Systems

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arxiv 2102.02625 v2 pith:IBFJCXSO submitted 2021-01-29 cs.SE cs.CYcs.LG

classification cs.SEcs.CYcs.LG
keywords templatessafetyargumentautonomousreportpresentssystemsystems
verification ladder T0 review T1 audit T2 compute T3 formal
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This report documents safety assurance argument templates to support the deployment and operation of autonomous systems that include machine learning (ML) components. The document presents example safety argument templates covering: the development of safety requirements, hazard analysis, a safety monitor architecture for an autonomous system including at least one ML element, a component with ML and the adaptation and change of the system over time. The report also presents generic templates for argument defeaters and evidence confidence that can be used to strengthen, review, and adapt the templates as necessary. This report is made available to get feedback on the approach and on the templates. This work was sponsored by the UK Dstl under the R-cloud framework.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Safety Cases: A Scalable Approach to Frontier AI Safety

    cs.CY 2025-02 accept novelty 4.0 of 10

    Structured safety arguments, called safety cases, can help frontier AI companies meet many of the Seoul Frontier AI Safety Commitments, though key methodological and technical gaps remain.

  2. A Taxonomy of Real-World Defeaters in Safety Assurance Cases

    cs.SE 2025-02 conditional novelty 4.0 of 10

    A systematic review yields a seven-category taxonomy of defeaters in safety assurance cases: logical, contextual, evidence-validity, requirements, structural, adversarial, and uncertainty.

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