2 citations · 3 across the 7 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…