activity
20242026
most citedClassEval-T: Evaluating Large Language Models in Class-Level Code Translation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SE2026

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…

cs.SE2026

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…

cs.SE2026

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…

cs.SE2025

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…

cs.SE2024★ 1 cited

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…