Quantifying the Epistemic Value of Verification: An Information‐Theoretic Approach

ABSTRACT System verification is a critical process that ensures components and systems meet their requirements at each integration level. Although verification significantly impacts project costs and schedules, its formal theoretical foundations have received relatively limited research attention compared to other systems engineering processes. Previous researchers have explored various metrics to optimize verification strategies, but these metrics often rely on programmatic factors like cost and utility rather than capturing verification's epistemic value—the fundamental ability to reduce uncertainty about requirement satisfaction. This paper introduces a novel theoretical framework that applies concepts from information theory to quantify the epistemic value of verification activities. By treating verification as an uncertainty reduction process, we leverage information‐theoretic measures such as entropy and information gain to evaluate how effectively different verification strategies illuminate whether requirements are truly satisfied. This framework provides a mathematical foundation for optimizing verification strategies based on their core function of generating knowledge about system performance, independent of external programmatic factors.