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arXiv — cs.AI preprintsInternational21 October 2026

When Models Edit Too Much: On the Fidelity of Minimal Code Edits

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arXiv:2609.04061v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used to edit existing code, but correctness alone is not enough: useful repairs should also be minimal, reviewable, and faithful to the original implementation. We study over-editing, the tendency of a model to rewrite code beyond what is required to fix a bug. We construct an evaluation framework from 400 BigCodeBench problems by injecting controlled AST-level corruptions into reference solutions, giving each repair task a known minimal patch. Across frontier LLMs, over-editing is widesprea
— arXiv — cs.AI preprints

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