3 citations · 7 across the 13 of their papers we have counts for
5 papers · 1 filter
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…
NARRepair: Non-Autoregressive Code Generation Model for Automatic Program Repair
Zhenyu Yang, Zhen Yang, Zhongxing Yu
With the advancement of deep learning techniques, the performance of Automatic Program Repair(APR) techniques has reached a new level. Previous deep learning-based APR techniques e…
Exploring and Unleashing the Power of Large Language Models in Automated Code Translation
Zhen Yang, Fang Liu, Zhongxing Yu +7
Code translation tools (transpilers) are developed for automatic source-to-source translation. Although learning-based transpilers have shown impressive enhancement against rule-ba…
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…