4 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.SE2023★ 4 cited
LLaMA-Reviewer: Advancing Code Review Automation with Large Language Models through Parameter-Efficient Fine-Tuning
Junyi Lu, Lei Yu, Xiaojia Li +2
The automation of code review activities, a long-standing pursuit in software engineering, has been primarily addressed by numerous domain-specific pre-trained models. Despite thei…
cs.SE2023
Automating Method Naming with Context-Aware Prompt-Tuning
Jie Zhu, Lingwei Li, Li Yang +2
Method names are crucial to program comprehension and maintenance. Recently, many approaches have been proposed to automatically recommend method names and detect inconsistent name…
cs.SE2022★ 1 cited
AUGER: Automatically Generating Review Comments with Pre-training Models
Lingwei Li, Li Yang, Huaxi Jiang +5
Code review is one of the best practices as a powerful safeguard for software quality. In practice, senior or highly skilled reviewers inspect source code and provide constructive…