Vulnerability Repair

Vulnerability repair research focuses on automatically fixing security flaws in software code, aiming to improve software security and reduce the burden on human developers. Current efforts heavily utilize large language models (LLMs), often enhanced with techniques like reinforcement learning and context-aware prompt tuning, to identify vulnerabilities and generate correct patches. While LLMs show promise, challenges remain in achieving high repair accuracy across diverse vulnerability types and programming languages, particularly for complex issues requiring deep understanding of code structure and logic; improved datasets and evaluation metrics are also active research areas.