1 citations · 2 across the 8 of their papers we have counts for
9 papers
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…
SWE-NFI: Studying and Benchmarking Coding Agents for Non-Functional Improvements
Pengyu Xue, He Yang Yuan, Xin Wang +6
Although coding agents have achieved impressive performance on correctness-oriented benchmarks, their ability to make behavior-preserving non-functional improvements (NFIs) remains…
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…
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…
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…