Dimensions overall score 7.0

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• Current EASA guidelines require demonstrating complete coverage of the AI/ML constituent's Operational Design Domain (ODD) with proof that no critical gaps exist within defined operational boundaries.technical 95%
• Existing methods struggle to provide the scalability and formal grounding necessary to satisfy the completeness criterion for ODD coverage in high-dimensional parameter spaces.limitation 90%
• Currently, no standardized engineering method exists to bridge the gap between abstract ODD definitions and verifiable evidence.limitation 90%
• The paper proposes a method that integrates parameter discretization, constraint-based filtering, and criticality-based dimension reduction into a structured, multi-step ODD coverage verification process.method 95%
• The proposed method is grounded in gathered simulation data from prior research on AI-based mid-air collision avoidance research.method 90%
• The method demonstrates a systematic engineering approach to defining and achieving coverage metrics that satisfy EASA's demand for completeness.result 85%
• The method enables the validation of ODD coverage in higher dimensions.result 85%
• The method advances a Safety-by-Design approach while complying with EASA's standards.method 80%

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