activity
20242026
most citedTowards Explainable Vulnerability Detection with Large Language Models

3 citations · 6 across the 9 of their papers we have counts for

collaborators

9 papers

cs.SE2026

Mitigating Package Hallucinations in Large Language Models via Model Editing

Shuhan Liu, Yukai Zhao, Xing Hu +3

Large language models (LLMs) have demonstrated strong capabilities in software engineering tasks, such as code generation, library recommendation, and dependency configuration. How…

cs.SE2026

Dependency-Guided Repository-Level C-to-Rust Translation with Reinforcement Alignment

Jia Feng, Wenjie Gan, Cuiyun Gao +5

Automating C-to-Rust migration is critical for improving software security without sacrificing performance. Traditional rule-based methods struggle with diverse C idioms, often pro…

cs.SE2026

RACE-Bench: A Reasoning-Augmented Benchmark for Repository-Level Code Agents on Feature Addition

Shuhan Liu, Zhiyi Zhao, Xing Hu +3

Repository-level code agents have shown strong promise in real-world feature addition tasks, making reliable evaluation of their capabilities increasingly important. However, exist…

cs.SE2025

Code Change Intention, Development Artifact and History Vulnerability: Putting Them Together for Vulnerability Fix Detection by LLM

Xu Yang, Wenhan Zhu, Michael Pacheco +4

Detecting vulnerability fix commits in open-source software is crucial for maintaining software security. To help OSS identify vulnerability fix commits, several automated approach…

cs.SE2025★ 1 cited

An Empirical Study of Retrieval-Augmented Code Generation: Challenges and Opportunities

Zezhou Yang, Sirong Chen, Cuiyun Gao +4

Code generation aims to automatically generate code snippets of specific programming language according to natural language descriptions. The continuous advancements in deep learni…

cs.SE2024★ 1 cited

Similar but Patched Code Considered Harmful -- The Impact of Similar but Patched Code on Recurring Vulnerability Detection and How to Remove Them

Zixuan Tan, Jiayuan Zhou, Xing Hu +3

Identifying recurring vulnerabilities is crucial for ensuring software security. Clone-based techniques, while widely used, often generate many false alarms due to the existence of…

cs.SE2024

Understanding Practitioners' Expectations on Clear Code Review Comments

Junkai Chen, Zhenhao Li, Qiheng Mao +3

The code review comment (CRC) is pivotal in the process of modern code review. It provides reviewers with the opportunity to identify potential bugs, offer constructive feedback, a…

cs.SE2024★ 3 cited

Towards Explainable Vulnerability Detection with Large Language Models

Qiheng Mao, Zhenhao Li, Xing Hu +3

Software vulnerabilities pose significant risks to the security and integrity of software systems. Although prior studies have explored vulnerability detection using deep learning…

cs.SE2024★ 1 cited

A Roadmap on Modern Code Review: Challenges and Opportunities

Zezhou Yang, Cuiyun Gao, Zhaoqiang Guo +4

Over the past decade, modern code review (MCR) has been established as a cornerstone of software quality assurance and a vital channel for knowledge transfer within development tea…