Exact Match (Functional Equivalence) is a critical evaluation metric for code translation and cross-language migration tasks in the field of Natural Language Processing. It determines whether the translated code is functionally equivalent to the target code (verified by test cases), reflecting the semantic fidelity of cross-language translation. It is typically reported as a percentage or a score between 0 and 1. This metric is widely used in relevant benchmarks and papers, effectively reflecting model performance in this dimension. Higher values indicate better performance.