collaborators

5 papers

cs.PL2026

Learning to Guarantee Type Correctness in Code Generation through Type-Guided Program Synthesis

Zhechong Huang, Zhao Zhang, Ruyi Ji +6

Language models have shown remarkable proficiency in code generation; nevertheless, ensuring type correctness remains a challenge. Although traditional methods, such as constrained…

cs.PL2025

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…

cs.SE2025

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…

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

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…