How Effective Are Neural Networks for Fixing Security Vulnerabilities

arXiv:2305.18607v2 Announce Type: replace-cross
Abstract: 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 …

arxiv automated automation code code completion cs.ai cs.cr cs.se language language models large llms networks neural networks program repair security security vulnerability source code task techniques vulnerabilities vulnerability