How Effective Are Neural Networks for Fixing Security Vulnerabilities
Yi Wu, Nan Jiang, Hung Viet Pham, Thibaud Lutellier, Jordan Davis, Lin Tan, Petr Babkin, Sameena Shah
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.
Topics & Concepts
Computer scienceTask (project management)Vulnerability (computing)Code (set theory)Software security assuranceSecure codingComputer securitySource codeSoftwareArtificial neural networkSoftware bugAutomationProgramming languageSoftware engineeringArtificial intelligenceInformation securityEngineeringSecurity serviceSet (abstract data type)Systems engineeringMechanical engineeringSoftware Testing and Debugging TechniquesSoftware Engineering ResearchSoftware Reliability and Analysis Research