collaborators

6 papers

cs.SE2026

TestDecision: Sequential Test Suite Generation via Greedy Optimization and Reinforcement Learning

Guoqing Wang, Chengran Yang, Xiaoxuan Zhou +4

With the rapid evolution of LLMs, automated software testing is witnessing a paradigm shift. While proprietary models like GPT-4o demonstrate impressive capabilities, their high de…

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

GramTrans: A Better Code Representation Approach in Code Generation

Zhao Zhang, Qingyuan Liang, Zeyu Sun +6

Code generation has shown great promise in assisting software development. A fundamental yet underexplored question is how the choice of code representation affects model performan…

cs.SE2025

Prompt Alchemy: Automatic Prompt Refinement for Enhancing Code Generation

Sixiang Ye, Zeyu Sun, Guoqing Wang +4

Code generation has emerged as a key task to automate software development by converting high-level descriptions into executable code. Large language models (LLMs) excel at this bu…

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…