2 citations · 2 across the 3 of their papers we have counts for
7 papers
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…
Grammar-Based Code Representation: Is It a Worthy Pursuit for LLMs?
Qingyuan Liang, Zhao Zhang, Zeyu Sun +9
Grammar serves as a cornerstone in programming languages and software engineering, providing frameworks to define the syntactic space and program structure. Existing research demon…
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…
Condor: A Code Discriminator Integrating General Semantics with Code Details
Qingyuan Liang, Zhao Zhang, Chen Liu +9
LLMs demonstrate significant potential across various software engineering tasks. However, they still face challenges in generating correct code on the first attempt when addressin…