As software systems increasingly rely on layered business rules, feature flags, and conditional workflows, validating logical correctness becomes more challenging than simply executing code paths. Teams often discover that tests pass while subtle decision errors still reach production, especially when multiple conditions influence a single outcome. This growing gap between execution and correctness is where modified condition decision coverage starts to surface in engineering discussions.In logic-heavy systems, a small change to one condition can silently alter behavior without triggering obvious failures. This makes traditional coverage metrics less effective at revealing risk, particularly in domains like finance, healthcare, or access control where decision accuracy matters deeply. Teams must therefore think more carefully about how they validate decision-making logic rather than relying solely on broad execution metrics.By paying closer attention to how conditions influence outcomes, teams can improve confidence in critical logic, reduce hidden defects, and make more informed decisions about test depth—strengthening overall software reliability without unnecessary overhead.
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