correspondence-review

To verify Lean model correspondence with source code, you audit the definitions to classify fidelity as exact, abstraction, approximation, or mismatch. This ensures formal models precisely mirror source code or correctly abstract over it before launching verification tasks.

Lean-source code correspondence classification compares Lean implementations against source code to detect and categorize divergences. It determines whether models are exact, abstracted, approximate, or mismatched, ensuring reliable formal verification and model suitability.

Assessing the impact of Lean definition divergences involves evaluating how mismatches or abstractions affect downstream verification tasks like differential testing. This impact assessment ensures divergences do not compromise the reliability of formal model checking.

Yes, you can audit Lean models across codebases in formal verification workflows. The process operates across your source code to detect divergences and determine if models are accurate or appropriately abstracted for reliable verification.

You need to check Lean model fidelity before running model checking when you want to ensure formal models precisely mirror source code or correctly abstract over it. This prevents inaccurate verification results caused by undetected model divergences.

The best way to categorize formal model fidelity is by comparing Lean implementations with source code to classify them as exact, abstraction, approximation, or mismatch. This categorization identifies divergences and evaluates their impact on verification reliability.