activity
20242026
collaborators

5 papers

cs.SE2026

Search-Induced Issues in Web-Augmented LLM Code Generation: Detecting and Repairing Error-Inducing Pages

Guoqing Wang, Zeyu Sun, Xiaofei Xie +4

Web-augmented large language models (LLMs) offer promising capabilities for automatic code generation. However, integrating live web search exposes models to unreliable or maliciou…

cs.SE2025

Directional Diffusion-Style Code Editing Pre-training

Qingyuan Liang, Zeyu Sun, Qihao Zhu +6

Code pre-trained models have shown promising effectiveness in various software engineering tasks. Among these tasks, many tasks are related to software evolution and/or code editin…

cs.SE2025

CupCleaner: A Hybrid Data Cleaning Approach for Comment Updating

Qingyuan Liang, Zeyu Sun, Qihao Zhu +4

Comment updating is an emerging task in software evolution that aims to automatically revise source code comments in accordance with code changes. This task plays a vital role in m…

cs.SE2025

Automatically Learning a Precise Measurement for Fault Diagnosis Capability of Test Cases

Yifan Zhao, Zeyu Sun, Guoqing Wang +5

Prevalent Fault Localization (FL) techniques rely on tests to localize buggy program elements. Tests could be treated as fuel to further boost FL by providing more debugging inform…

cs.SE2024

Do Advanced Language Models Eliminate the Need for Prompt Engineering in Software Engineering?

Guoqing Wang, Zeyu Sun, Zhihao Gong +5

Large Language Models (LLMs) have significantly advanced software engineering (SE) tasks, with prompt engineering techniques enhancing their performance in code-related areas. Howe…