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    Publications

Journal Article

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

Documentation Topics

Published: June 26, 2025
Citation: Computer (IEEE Computer) vol. 58, no. 7, (July 2025) pp. 122-128

Author(s)

Lan Zhang (Northern Arizona University), Anoop Singhal (NIST), Qingtian Zou (University of Texas Southwestern Medical Center at Dallas), Xiaoyan Sun (Worcester Polytechnic Institute), Peng Liu (Penn State University)

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.

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.

Keywords

Large Language Models; program repair; deep learning
Control Families

None selected

Documentation

Publication:
https://doi.org/10.1109/MC.2025.3527407
Preprint (pdf)

Supplemental Material:
None available

Document History:
06/26/25: Journal Article (Final)

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