Towards higher quality software vulnerability data using LLM-based patch filtering

doi:10.1016/j.jss.2025.112581

Towards higher quality software vulnerability data using LLM-based patch filtering

2025-07-31

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DOI：10.1016/j.jss.2025.112581

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High-quality vulnerability patch data is essential for understanding vulnerabilities in software systems. Accurate patch data sheds light on the nature of vulnerabilities, their origins, and effective remediation strategies. However, current data collection efforts prioritize rapid release over quality, leading to patches that are incomplete or contain extraneous changes. In addition to supporting vulnerability analysis, high-quality patch data improves automatic vulnerability prediction models, which require reliable inputs to predict issues in new or existing code.

Keywords:

vulnerability patch data

software systems

remediation strategies

automatic vulnerability prediction

data quality

Towards higher quality software vulnerability data using LLM-based patch filtering

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