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Within the realm of software engineering, specialized tasks on code, such as program repair, present unique challenges, necessitating fine-tuning Large language models~(LLMs) to unlock state-of-the-art performance.
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Lora: Low-rank adaptation of large language models
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Cure: Code-aware neural machine translation for automatic program repair. In 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) . IEEE, 1161–1173
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VarFix: balancing edit expressiveness and search effectiveness in automated program repair. In Proceedings of the 29th ACM joint meeting on European software engineering conference and symposium on the foundations of software engineering . 354–366
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Improving automatically generated code from Codex via Automated Program Repair
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Incoder: A generative model for code infilling and synthesis
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VulRepair: a T5-based automated software vulnerability repair. In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering . 935–947
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Unixcoder: Unified cross-modal pre-training for code representation
Daya Guo, Shuai Lu, Nan Duan, Yanlin Wang, Ming Zhou, and Jian Yin. 2022 · 2022
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Large language models are reasoning teachers
Namgyu Ho, Laura Schmid, and Se-Young Yun. 2022 · 2022
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Review4Repair: Code review aided automatic program repairing
Faria Huq, Masum Hasan, Md Mahim Anjum Haque, Sazan Mahbub, Anindya Iqbal, and Toufique Ahmed. 2022 · 2022
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A Hazard Analysis Framework for Code Synthesis Large Language Models
Heidy Khlaaf, Pamela Mishkin, Joshua Achiam, Gretchen Krueger, and Miles Brundage. 2022 · 2022
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Fine-tuning gpt-2 to patch programs, is it worth it?. In International Conference on Computational Science and Its Applications . Springer, 79–91
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Codegen: An open large language model for code with multi-turn program synthesis
Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong. 2022 · 2022
Cited alongside, same era.
Trust enhancement issues in program repair. In Proceedings of the 44th International Conference on Software Engineering . 2228–2240
Yannic Noller, Ridwan Shariffdeen, Xiang Gao, and Abhik Roychoudhury. 2022 · 2022
Cited alongside, same era.
Can OpenAI’s codex fix bugs? an evaluation on QuixBugs. In Proceedings of the Third International Workshop on Automated Program Repair . 69–75
Julian Aron Prenner, Hlib Babii, and Romain Robbes. 2022 · 2022
Cited alongside, same era.
Is this change the answer to that problem? correlating descriptions of bug and code changes for evaluating patch correctness. In Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering . 1–13
Haoye Tian, Xunzhu Tang, Andrew Habib, Shangwen Wang, Kui Liu, Xin Xia, Jacques Klein, and Tegawendé F Bissyandé. 2022 · 2022
Cited alongside, same era.
Just-in-Time Security Patch Detection–LLM At the Rescue for Data Augmentation
Xunzhu Tang, Zhenghan Chen, Kisub Kim, Haoye Tian, Saad Ezzini, and Jacques Klein. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
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Creating a Coding Assistant with StarCoder
Lewis Tunstall, Nathan Lambert, Nazneen Rajani, Edward Beeching, Teven Le Scao, Leandro von Werra, Sheon Han, Philipp Schmid, and Alexander Rush. 2023 · 2023
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Conversational automated program repair
Chunqiu Steven Xia and Lingming Zhang. 2023a · 2023
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Keep the Conversation Going: Fixing 162 out of 337 bugs for $0.42 each using ChatGPT
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Improving automated program repair with domain adaptation
Armin Zirak and Hadi Hemmati. 2022 · 2022
Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Cited alongside, same era.
A study on prompt design, advantages and limitations of chatgpt for deep learning program repair
Jialun Cao, Meiziniu Li, Ming Wen, and Shing-chi Cheung. 2023 · 2023
Cited alongside, same era.
Automated repair of programs from large language models. In 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) . IEEE, 1469–1481
Zhiyu Fan, Xiang Gao, Martin Mirchev, Abhik Roychoudhury, and Shin Hwei Tan. 2023 · 2023
Cited alongside, same era.
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes. In The 61st Annual Meeting Of The Association For Computational Linguistics
Cheng-yu Hsieh, Chun-liang Li, Chih-kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alex Ratner, Ranjay Krishna, Chen-yu Lee, and Tomas Pfister. 2023 · 2023
Cited alongside, same era.
An empirical study on fine-tuning large language models of code for automated program repair. In 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 1162–1174
Kai Huang, Xiangxin Meng, Jian Zhang, Yang Liu, Wenjie Wang, Shuhao Li, and Yuqing Zhang. 2023 · 2023
Cited alongside, same era.
Neftune: Noisy embeddings improve instruction finetuning
Neel Jain, Ping-yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, et al · 2023
Cited alongside, same era.
Impact of Code Language Models on Automated Program Repair. In Proceedings of the 45th International Conference on Software Engineering (Melbourne, Victoria, Australia) (ICSE ’23) . IEEE Press, 1430–1442
Nan Jiang, Kevin Liu, Thibaud Lutellier, and Lin Tan. 2023a · 2023
Cited alongside, same era.
Chunqiu Steven Xia and Lingming Zhang. 2023b · 2023
Later among the works it cites.
CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Evaluations on HumanEval-X
Qinkai Zheng, Xiao Xia, Xu Zou, Yuxiao Dong, Shan Wang, Yufei Xue, Zihan Wang, Lei Shen, Andi Wang, Yang Li, Teng Su, Zhilin Yang, and Jie Tang. 2023 · 2023
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Repairagent: An autonomous, llm-based agent for program repair
Islem Bouzenia, Premkumar Devanbu, and Michael Pradel. 2024 · 2024
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Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2024 · 2024
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Prompting Is All You Need: Automated Android Bug Replay with Large Language Models. In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering . 1–13
Sidong Feng and Chunyang Chen. 2024 · 2024
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Wenqiang Luo, Jacky Wai Keung, Boyang Yang, He Ye, Claire Le Goues, Tegawende F. Bissyande, Haoye Tian, and Bach Le. 2024 · 2024
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Domain knowledge matters: Improving prompts with fix templates for repairing python type errors. In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering . 1–13
Yun Peng, Shuzheng Gao, Cuiyun Gao, Yintong Huo, and Michael Lyu. 2024 · 2024
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Practical tips for finetuning llms using lora (low-rank adaptation)
Sebastian Raschka. 2024 · 2024
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CodeAgent: Autonomous Communicative Agents for Code Review. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing . Association for Computational Linguistics, Miami, Florida, USA, 11279–11313
Xunzhu Tang, Kisub Kim, Yewei Song, Cedric Lothritz, Bei Li, Saad Ezzini, Haoye Tian, Jacques Klein, and Tegawendé F. Bissyandé. 2024 · 2024
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LoRA-Pro: Are Low-Rank Adapters Properly Optimized?
Zhengbo Wang, Jian Liang, Ran He, Zilei Wang, and Tieniu Tan. 2024 · 2024
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Pydex: Repairing bugs in introductory python assignments using llms
Jialu Zhang, José Pablo Cambronero, Sumit Gulwani, Vu Le, Ruzica Piskac, Gustavo Soares, and Gust Verbruggen. 2024a · 2024
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A Systematic Literature Review on Large Language Models for Automated Program Repair
Quanjun Zhang, Chunrong Fang, Yang Xie, YuXiang Ma, Weisong Sun, and Yun Yang Zhenyu Chen. 2024b · 2024
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, et al · 2025
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Wenqiang Luo, Jacky Wai Keung, Boyang Yang, Jacques Klein, Tegawende F. Bissyande, Haoye Tian, and Bach Le. 2025 · 2025
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You Don’t Have to Say Where to Edit! jLED–Joint Learning to Localize and Edit Source Code
Weiguo Pian, Yinghua Li, Haoye Tian, Tiezhu Sun, Yewei Song, Xunzhu Tang, Andrew Habib, Jacques Klein, and Tegawendé F Bissyandé. 2025 · 2025
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Logic-rl: Unleashing llm reasoning with rule-based reinforcement learning
Tian Xie, Zitian Gao, Qingnan Ren, Haoming Luo, Yuqian Hong, Bryan Dai, Joey Zhou, Kai Qiu, Zhirong Wu, and Chong Luo. 2025 · 2025
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Enhancing Repository-Level Software Repair via Repository-Aware Knowledge Graphs
Boyang Yang, Haoye Tian, Jiadong Ren, Shunfu Jin, Yang Liu, Feng Liu, and Bach Le. 2025 · 2025
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Demystifying Long Chain-of-Thought Reasoning in LLMs
Edward Yeo, Yuxuan Tong, Morry Niu, Graham Neubig, and Xiang Yue. 2025 · 2025
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