Fetching the paper…
Reading the bibliography…
In this paper, we first show that increases in beam size, even for small-sized LLMs (1B-7B params), require extensive GPU usage, leading to up to 80% of recurring crashes due to memory overloads in LLM-based APR.
Sequencer: Sequence-to-sequence learning for end-to-end program repair
Zimin Chen, Steve James Kommrusch, Michele Tufano, Louis-Noël Pouchet, Denys Poshyvanyk, and Martin Monperrus. 2021a · 1959
Earlier work this paper cites.
Reinforcement learning: A survey
Leslie Pack Kaelbling, Michael L Littman, and Andrew W Moore. 1996 · 1996
Earlier work this paper cites.
Bandit based monte-carlo planning. In European conference on machine learning . Springer, 282–293
Levente Kocsis and Csaba Szepesvári. 2006 · 2006
Earlier work this paper cites.
Reinforcement learning
Marco A Wiering and Martijn Van Otterlo. 2012 · 2012
Earlier work this paper cites.
Boa: A language and infrastructure for analyzing ultra-large-scale software repositories. In 2013 35th International Conference on Software Engineering (ICSE) . IEEE, 422–431
Robert Dyer, Hoan Anh Nguyen, Hridesh Rajan, and Tien N Nguyen. 2013 · 2013
Earlier work this paper cites.
Efficient automated program repair through fault-recorded testing prioritization. In 2013 IEEE International Conference on Software Maintenance . IEEE, 180–189
Yuhua Qi, Xiaoguang Mao, and Yan Lei. 2013 · 2013
Earlier work this paper cites.
Defects4J: A database of existing faults to enable controlled testing studies for Java programs. In Proceedings of the 23rd International Symposium on Software Testing and Analysis (ISSTA) . 437–440
René Just, Darioush Jalali, and Michael D Ernst. 2014 · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
Earlier work this paper cites.
An analysis of patch plausibility and correctness for generate-and-validate patch generation systems. In Proceedings of the 2015 ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) . Association for Computing Machinery, 24–36
Zichao Qi, Fan Long, Sara Achour, and Martin Rinard. 2015 · 2015
Earlier work this paper cites.
relifix: Automated repair of software regressions. In 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering , Vol. 1. IEEE, 471–482
Shin Hwei Tan and Abhik Roychoudhury. 2015 · 2015
Earlier work this paper cites.
History driven program repair. In Proceedings of the 23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER) . IEEE, 213–224
Xuan Bach D Le, David Lo, and Claire Le Goues. 2016 · 2016
Earlier work this paper cites.
S3: syntax-and semantic-guided repair synthesis via programming by examples. In Proceedings of the 11th Joint Meeting on Foundations of Software Engineering (ESEC/FSE) . Association for Computing Machinery, 593–604
Xuan-Bach D Le, Duc-Hiep Chu, David Lo, Claire Le Goues, and Willem Visser. 2017 · 2017
Earlier work this paper cites.
Mastering chess and shogi by self-play with a general reinforcement learning algorithm
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, et al · 2017
Earlier work this paper cites.
Leveraging syntax-related code for automated program repair. In 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 660–670
Qi Xin and Steven P Reiss. 2017 · 2017
Earlier work this paper cites.
Overfitting in semantics-based automated program repair. In Proceedings of the 40th International Conference on Software Engineering . 163–163
Xuan-Bach D Le, Ferdian Thung, David Lo, and Claire Le Goues. 2018 · 2018
Earlier work this paper cites.
Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto. 2018 · 2018
Earlier work this paper cites.
Context-aware patch generation for better automated program repair. In Proceedings of the 40th international conference on software engineering . 1–11
Ming Wen, Junjie Chen, Rongxin Wu, Dan Hao, and Shing-Chi Cheung. 2018 · 2018
Earlier work this paper cites.
Getafix: Learning to fix bugs automatically
Johannes Bader, Andrew Scott, Michael Pradel, and Satish Chandra. 2019 · 2019
Earlier work this paper cites.
Empirical review of java program repair tools: A large-scale experiment on 2,141 bugs and 23,551 repair attempts. In Proceedings of the 2019 27th ACM joint meeting on european software engineering conference and symposium on the foundations of software engineering . 302–313
Thomas Durieux, Fernanda Madeiral, Matias Martinez, and Rui Abreu. 2019 · 2019
Earlier work this paper cites.
Practical program repair via bytecode mutation. In Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis . 19–30
Ali Ghanbari, Samuel Benton, and Lingming Zhang. 2019 · 2019
Earlier work this paper cites.
Automated program repair
Claire Le Goues, Michael Pradel, and Abhik Roychoudhury. 2019 · 2019
Earlier work this paper cites.
On reliability of patch correctness assessment. In 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) . IEEE, 524–535
Xuan-Bach D Le, Lingfeng Bao, David Lo, Xin Xia, Shanping Li, and Corina Pasareanu. 2019 · 2019
Earlier work this paper cites.
TBar: revisiting template-based automated program repair. In Proceedings of the 28th International Symposium on Software Testing and Analysis (ISSTA) . Association for Computing Machinery, 31–42
Kui Liu, Anil Koyuncu, Dongsun Kim, and Tegawendé F Bissyandé. 2019 · 2019
Earlier work this paper cites.
Sapfix: Automated end-to-end repair at scale. In 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP) . IEEE, 269–278
Alexandru Marginean, Johannes Bader, Satish Chandra, Mark Harman, Yue Jia, Ke Mao, Alexander Mols, and Andrew Scott. 2019 · 2019
Earlier work this paper cites.
An empirical study on learning bug-fixing patches in the wild via neural machine translation
Michele Tufano, Cody Watson, Gabriele Bavota, Massimiliano Di Penta, Martin White, and Denys Poshyvanyk. 2019 · 2019
Earlier work this paper cites.
The pile: An 800gb dataset of diverse text for language modeling
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, et al · 2020
Earlier work this paper cites.
On the efficiency of test suite based program repair: A systematic assessment of 16 automated repair systems for java programs. In Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering (ICSE) . Association for Computing Machinery, 615–627
Kui Liu, Shangwen Wang, Anil Koyuncu, Kisub Kim, Tegawendé F Bissyandé, Dongsun Kim, Peng Wu, Jacques Klein, Xiaoguang Mao, and Yves Le Traon. 2020 · 2020
Earlier work this paper cites.
Coconut: combining context-aware neural translation models using ensemble for program repair. In Proceedings of the 29th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) . IEEE, 101–114
Thibaud Lutellier, Hung Viet Pham, Lawrence Pang, Yitong Li, Moshi Wei, and Lin Tan. 2020 · 2020
Earlier work this paper cites.
Fast and precise on-the-fly patch validation for all. In 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) . IEEE, 1123–1134
Lingchao Chen, Yicheng Ouyang, and Lingming Zhang. 2021b · 2021
Cited alongside, same era.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
Cited alongside, same era.
CURE: Code-Aware Neural Machine Translation for Automatic Program Repair. In Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering (ICSE) . IEEE, 1161–1173
Nan Jiang, Thibaud Lutellier, and Lin Tan. 2021 · 2021
Cited alongside, same era.
SimTyper: sound type inference for Ruby using type equality prediction
Milod Kazerounian, Jeffrey S Foster, and Bonan Min. 2021 · 2021
Cited alongside, same era.
On the introduction of automatic program repair in Bloomberg
Is your code generated by chatgpt really correct? rigorous evaluation of large language models for code generation
Jiawei Liu, Chunqiu Steven Xia, Yuyao Wang, and Lingming Zhang. 2023 · 2023
Later among the works it cites.
Template-based neural program repair. In 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) . IEEE, 1456–1468
Xiangxin Meng, Xu Wang, Hongyu Zhang, Hailong Sun, Xudong Liu, and Chunming Hu. 2023 · 2023
Later among the works it cites.
Enhancing Automated Program Repair through Fine-tuning and Prompt Engineering
Rishov Paul, Md Mohib Hossain, Mohammed Latif Siddiq, Masum Hasan, Anindya Iqbal, and Joanna CS Santos. 2023 · 2023
Later among the works it cites.
Code llama: Open foundation models for code
Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Tal Remez, Jérémy Rapin, et al · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Serkan Kirbas, Etienne Windels, Olayori McBello, Kevin Kells, Matthew Pagano, Rafal Szalanski, Vesna Nowack, Emily Rowan Winter, Steve Counsell, David Bowes, et al · 2021
Cited alongside, same era.
Refixar: Multi-version reasoning for automated repair of regression errors. In 2021 IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE) . IEEE, 162–172
Xuan-Bach D Le and Quang Loc Le. 2021 · 2021
Cited alongside, same era.
Usability and aesthetics: Better together for automated repair of web pages. In 2021 IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE) . IEEE, 173–183
Thanh Le-Cong, Xuan Bach D Le, Quyet Thang Huynh, and Phi Le Nguyen. 2021 · 2021
Cited alongside, same era.
Megadiff: A dataset of 600k java source code changes categorized by diff size
Martin Monperrus, Matias Martinez, He Ye, Fernanda Madeiral, Thomas Durieux, and Zhongxing Yu. 2021 · 2021
Cited alongside, same era.
A syntax-guided edit decoder for neural program repair. In Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) . Association for Computing Machinery, 341–353
Qihao Zhu, Zeyu Sun, Yuan-an Xiao, Wenjie Zhang, Kang Yuan, Yingfei Xiong, and Lu Zhang. 2021 · 2021
Cited alongside, same era.
Few-shot training llms for project-specific code-summarization. In Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering . 1–5
Toufique Ahmed and Premkumar Devanbu. 2022 · 2022
Cited alongside, same era.
Program repair with repeated learning
Liushan Chen, Yu Pei, Minxue Pan, Tian Zhang, Qixin Wang, and Carlo A Furia. 2022 · 2022
Cited alongside, same era.
Incoder: A generative model for code infilling and synthesis
Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, and Mike Lewis. 2022 · 2022
Cited alongside, same era.
André Silva, Sen Fang, and Martin Monperrus. 2023 · 2023
Later among the works it cites.
Copiloting the copilots: Fusing large language models with completion engines for automated program repair. In Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering . 172–184
Yuxiang Wei, Chunqiu Steven Xia, and Lingming Zhang. 2023 · 2023
Later among the works it cites.
How do developers really feel about bug fixing? Directions for automatic program repair
Emily Winter, David Bowes, Steve Counsell, Tracy Hall, Sæmundur Haraldsson, Vesna Nowack, and John Woodward. 2023 · 2023
Later among the works it cites.
Revisiting the plastic surgery hypothesis via large language models
Chunqiu Steven Xia, Yifeng Ding, and Lingming Zhang. 2023a · 2023
Later among the works it cites.
Automated program repair in the era of large pre-trained language models. In Proceedings of the 45th International Conference on Software Engineering (ICSE 2023). Association for Computing Machinery
Chunqiu Steven Xia, Yuxiang Wei, and Lingming Zhang. 2023c · 2023
Later among the works it cites.
Keep the Conversation Going: Fixing 162 out of 337 bugs for 0.42 each using ChatGPT
Chunqiu Steven Xia and Lingming Zhang. 2023 · 2023
Later among the works it cites.
Gamma: Revisiting template-based automated program repair via mask prediction. In 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 535–547
Quanjun Zhang, Chunrong Fang, Tongke Zhang, Bowen Yu, Weisong Sun, and Zhenyu Chen. 2023b · 2023
Later among the works it cites.
Repairagent: An autonomous, llm-based agent for program repair
Islem Bouzenia, Premkumar Devanbu, and Michael Pradel. 2024 · 2024
Closest in time.
Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2024 · 2024
Closest in time.
Sequential beam search(a.k.a Low-memory beam search)
Saibo Geng & HuggingFace’s developers. 2024 · 2024
Closest in time.
Qwen2. 5-Coder Technical Report
Binyuan Hui, Jian Yang, Zeyu Cui, Jiaxi Yang, Dayiheng Liu, Lei Zhang, Tianyu Liu, Jiajun Zhang, Bowen Yu, Kai Dang, et al · 2024
Closest in time.
Enhancing the Efficiency of Automated Program Repair via Greybox Analysis. In 39th IEEE/ACM International Conference on Automated Software Engineering (ASE 2024)
YoungJae Kim, Yechan Park, Seungheon Han, and Jooyong Yi. 2024 · 2024
Closest in time.
Using an llm to help with code understanding. In Proceedings of the IEEE/ACM 46th International Conference on Software Engineering . 1–13
Daye Nam, Andrew Macvean, Vincent Hellendoorn, Bogdan Vasilescu, and Brad Myers. 2024 · 2024
Closest in time.
Encoding Version History Context for Better Code Representation
Huy Nguyen, Christoph Treude, and Patanamon Thongtanunam. 2024 · 2024
Closest in time.
Accelerating patch validation for program repair with interception-based execution scheduling
Yuan-An Xiao, Chenyang Yang, Bo Wang, and Yingfei Xiong. 2024 · 2024
Closest in time.
ITER: Iterative Neural Repair for Multi-Location Patches. In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering . 1–13
He Ye and Martin Monperrus. 2024 · 2024
Closest in time.
ThinkRepair: Self-Directed Automated Program Repair
Xin Yin, Chao Ni, Shaohua Wang, Zhenhao Li, Limin Zeng, and Xiaohu Yang. 2024 · 2024
Closest in time.
AutoCodeRover: Autonomous Program Improvement
Yuntong Zhang, Haifeng Ruan, Zhiyu Fan, and Abhik Roychoudhury. 2024 · 2024
Closest in time.
Benchmarking and Categorizing the Performance of Neural Program Repair Systems for Java
Wenkang Zhong, Chuanyi Li, Kui Liu, Jidong Ge, Bin Luo, Tegawendé F Bissyandé, and Vincent Ng. 2024 · 2024
Closest in time.
Bigcodebench: Benchmarking code generation with diverse function calls and complex instructions
Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, Han Hu, Wenhao Yu, Ratnadira Widyasari, Imam Nur Bani Yusuf, Haolan Zhan, Junda He, Indraneil Paul, et al · 2024
Closest in time.
Improving automated program repair with domain adaptation
Armin Zirak and Hadi Hemmati. 2024 · 2024
Closest in time.
Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testing
Thanh Le-Cong, Thanh-Dat Nguyen, Bach Le, and Toby Murray. 2025 · 2025
Closest in time.
ExpressAPR: Efficient patch validation for java automated program repair systems. In 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 2038–2041
Yuan-An Xiao, Chenyang Yang, Bo Wang, and Yingfei Xiong. 2023 · 2041
Closest in time.