9 citations · 10 across the 4 of their papers we have counts for
5 papers
VulRTex: A Reasoning-Guided Approach to Identify Vulnerabilities from Rich-Text Issue Report
Ziyou Jiang, Mingyang Li, Guowei Yang +2
Software vulnerabilities exist in open-source software (OSS), and the developers who discover these vulnerabilities may submit issue reports (IRs) to describe their details. Securi…
EXPEREPAIR: Dual-Memory Enhanced LLM-based Repository-Level Program Repair
Fangwen Mu, Junjie Wang, Lin Shi +3
Automatically repairing software issues remains a fundamental challenge at the intersection of software engineering and AI. Although recent advances in Large Language Models (LLMs)…
CodePurify: Defend Backdoor Attacks on Neural Code Models via Entropy-based Purification
Fangwen Mu, Junjie Wang, Zhuohao Yu +4
Neural code models have found widespread success in tasks pertaining to code intelligence, yet they are vulnerable to backdoor attacks, where an adversary can manipulate the victim…
PatUntrack: Automated Generating Patch Examples for Issue Reports without Tracked Insecure Code
Ziyou Jiang, Lin Shi, Guowei Yang +1
Security patches are essential for enhancing the stability and robustness of projects in the software community. While vulnerabilities are officially expected to be patched before…
ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification
Fangwen Mu, Lin Shi, Song Wang +5
We introduce a novel framework named ClarifyGPT, which aims to enhance code generation by empowering LLMs with the ability to identify ambiguous requirements and ask targeted clari…