Towards a compositional semantics for quantitative confidence assessment in assurance arguments
For practitioners and researchers in safety-critical systems assurance, this work addresses the lack of operational semantics for deriving confidence in assurance arguments, but it is an incremental extension of existing Subjective Logic-based approaches.
The paper proposes a compositional semantics for quantitative confidence assessment in assurance arguments by representing argument elements as Subjective Logic opinions and mapping relations to SL operators, enabling overall confidence propagation. The approach provides explicit warrants, context handling, provenance, and GSN compatibility.
Assurance arguments provide a clear and structured way to explain why stakeholders should trust that a system satisfies certain properties, yet widely used notations, e.g.Goal Structuring Notation (GSN), typically lack an operational semantics for deriving assurance confidence. Existing approaches address structure and soundness but largely reason over truth values, not over confidence in the justification of claims. Subjective Logic (SL) offers a calculus of belief, disbelief, and uncertainty with operators for combining opinions, enabling confidence propagation under incomplete, conflicting, or subjective evidence. However, existing SL-based approaches do not provide a uniform, compositional semantics that covers all argument elements and relations to enable overall confidence assessment. We propose a confidence semantics that represents argument elements as SL opinions and maps relations between elements to SL operators modelling how confidence flows, effectively turning the argument into an analyzable confidence network. The approach provides explicit warrants, principled handling of context, preserved provenance, and compatibility with GSN, along with practical guidance using an exemplary assurance confidence assessment.