An Empirical Study on Fine-Tuning Large Language Models of Code for Automated Program Repair

The advent of large language models (LLMs) has opened up new opportunities for automated program repair (APR). In particular, some recent studies have explored how to leverage large language models of code (LLMCs) for program repair tasks and show promising results. However, most of them adopt the z...

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Vydané v:	IEEE/ACM International Conference on Automated Software Engineering : [proceedings] s. 1162 - 1174
Hlavní autori:	Huang, Kai, Meng, Xiangxin, Zhang, Jian, Liu, Yang, Wang, Wenjie, Li, Shuhao, Zhang, Yuqing
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 11.09.2023
Predmet:	Automated Program Repair Benchmark testing Codes Computer bugs Computer languages Fine-Tuning Java Large Language Models of Code Maintenance engineering Measurement Neural Machine Translation
ISSN:	2643-1572
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