1 citations · 2 across the 10 of their papers we have counts for
13 papers
State-Aware Generation of Deployable Websites from Visual Prototypes and Requirements
Ruwei Pan, Junlei Shen, Linhao Wu +7
Generating deployable websites from visual prototypes and textual requirements is increasingly feasible with multimodal models, yet keeping generated projects consistent with their…
Do Modifications Made by Coding Agents Make Subsequent Software Maintenance Harder?
Ruwei Pan, John Zhang, Linhao Wu +3
Coding agents increasingly maintain repositories over time, where each change becomes the starting point for subsequent tasks. Yet existing benchmarks either start tasks from devel…
CausalRepair: Bridging the Causality Gap in Large Language Model-Based Automated Program Repair via Dual-Slicing
Linhao Wu, Yizhou Chen, Zhen Yang +2
Automated Program Repair (APR) has recently benefited from Large Language Models (LLMs), yet their effectiveness heavily depends on repair context. Existing LLM-based APR methods s…
Porting Declarative UI to HarmonyOS: A Heuristic-guided Approach for lightweight LLMs
Kunwu Zheng, Pengyu Xue, Zhen Yang +10
As an emerging operating system, HarmonyOS has a significant demand for software migration, where the User Interface (UI) translation accounts for a critical link. However, recent…
DebugRepair: Enhancing LLM-Based Automated Program Repair via Self-Directed Debugging
Linhao Wu, Yifei Pei, Zhen Yang +9
Automated Program Repair (APR) has benefited from the code understanding and generation capabilities of Large Language Models (LLMs). Existing feedback-based APR methods iterativel…
Persistent Cross-Attempt State Optimization for Repository-Level Code Generation
Ruwei Pan, Jiangshuai Wang, Qisheng Zhang +6
Large language models (LLMs) have achieved substantial progress in repository-level code generation. However, solving the same repository-level task often requires multiple attempt…
Toward Executable Repository-Level Code Generation via Environment Alignment
Ruwei Pan, Junlei Shen, Linhao Wu +5
Large language models (LLMs) have achieved strong performance on code generation, but existing methods still struggle with repository-level code generation under executable validat…
Fixturize: Bridging the Fixture Gap in Test Generation
Chengyi Wang, Pengyu Xue, Zhen Yang +8
Current Large Language Models (LLMs) have advanced automated unit test generation but face a critical limitation: they often neglect to construct the necessary test fixtures, which…
TransLibEval: Demystify Large Language Models' Capability in Third-party Library-targeted Code Translation
Pengyu Xue, Kunwu Zheng, Zhen Yang +11
In recent years, Large Language Models (LLMs) have been widely studied in the code translation field on the method, class, and even repository levels. However, most of these benchm…
DISTINCT: A Description-Guided Branch-Consistency Analysis Framework for Non-Regressive Test Case Generation
Pengyu Xue, Yuxiang Zhang, Zhen Yang +5
Automated test-generation research overwhelmingly assumes the correctness of focal methods, yet practitioners routinely face non-regression scenarios where the focal method may be…
ClassEval-T: Evaluating Large Language Models in Class-Level Code Translation
Pengyu Xue, Linhao Wu, Zhen Yang +9
In recent years, Large Language Models (LLMs) have dramatically advanced the performance of automated code translation, making their computational accuracy score reach up to over 8…
Exploring and Lifting the Robustness of LLM-powered Automated Program Repair with Metamorphic Testing
Pengyu Xue, Linhao Wu, Zhen Yang +8
In recent years, Large language model-powered Automated Program Repair (LAPR) techniques have achieved state-of-the-art bug-fixing performance and have been pervasively applied and…
Automated Commit Message Generation with Large Language Models: An Empirical Study and Beyond
Pengyu Xue, Linhao Wu, Zhongxing Yu +5
Commit Message Generation (CMG) approaches aim to automatically generate commit messages based on given code diffs, which facilitate collaboration among developers and play a criti…