How Effective Are Neural Networks for Fixing Security Vulnerabilities. (arXiv:2305.18607v1 [cs.SE])

Security vulnerability repair is a difficult task that is in dire need of
automation. Two groups of techniques have shown promise: (1) large code
language models (LLMs) that have been pre-trained on source code for tasks such
as code completion, and (2) automated program repair (APR) techniques that use
deep learning (DL) models to automatically fix software bugs.

This paper is the first to study and compare Java vulnerability repair
capabilities of LLMs and DL-based APR models. The contributions include …

automated automation code code completion language language models large llms networks neural networks program repair security security vulnerability source code task techniques vulnerabilities vulnerability