LLaMA-Reviewer: Advancing Code Review Automation with Large Language Models through Parameter-Efficient Fine-Tuning

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 their success, these models frequently demand extensive resources for pre-training from scratch. In contrast, Large Language...

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Veröffentlicht in:	Proceedings - International Symposium on Software Reliability Engineering S. 647 - 658
Hauptverfasser:	Lu, Junyi, Yu, Lei, Li, Xiaojia, Yang, Li, Zuo, Chun
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 09.10.2023
Schlagworte:	Automation Code Review Automation Codes Deep Learning Large Language Models (LLMs) LLaMA Parameter-Efficient Fine-Tuning (PEFT) Quality assurance Software engineering Software Quality Assurance Software reliability Task analysis Tuning
ISSN:	2332-6549
Online-Zugang:	Volltext
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