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PUBLICATIONS

Can AI Fix Buggy Code? Exploring the Use of Large Language Models in Automated Program Repair

Published

Author(s)

Lan Zhang, Anoop Singhal, Qingtian Zou, Xiaoyan Sun, Peng Liu

Abstract

This article reviews the current human–large language models collaboration approach to bug fixing and points out the research directions toward (the development of) autonomous program repair artificial intelligence agents.
Citation
Computer (IEEE Computer)
Volume
58
Issue
7
Pub Type
Journals

Download Paper

https://doi.org/10.1109/MC.2025.3527407
Local Download

Keywords

Large Language Models, program repair, deep learning
Information technology and Artificial intelligence

Citation

Zhang, L. , Singhal, A. , Zou, Q. , Sun, X. and Liu, P. (2025), Can AI Fix Buggy Code? Exploring the Use of Large Language Models in Automated Program Repair, Computer (IEEE Computer), [online], https://doi.org/10.1109/MC.2025.3527407, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=959070 (Accessed July 4, 2025)

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Created June 26, 2025, Updated July 2, 2025
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