AI RESEARCH
A Subjective Logic-based method for runtime confidence updates in safety arguments
arXiv CS.AI
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ArXi:2605.22530v1 Announce Type: new We present a method for dynamic quantitative assurance that enhances static safety cases with continuous, runtime-driven confidence updates. The method quantifies and propagates confidence across the development lifecycle by integrating design-time evidence and windowed runtime Safety Performance Indicators (SPIs) within a single Subjective Logic (SL)-based assurance case.