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Automated Program Repair (APR) aspires to automatically generate patches for an input buggy program.
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
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CodeBERT: A Pre-Trained Model for Programming and Natural Languages
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Language Models are Few-Shot Learners
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On the Accuracy of Spectrum-based Fault Localization. In Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION (TAICPART-MUTATION 2007) . 89–98
Rui Abreu, Peter Zoeteweij, and Arjan J.C. van Gemund. 2007 · 2007
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Extraction of Bug Localization Benchmarks from History. In Proceedings of the Twenty-Second IEEE/ACM International Conference on Automated Software Engineering (Atlanta, Georgia, USA) (ASE ’07) . Association for Computing Machinery, New York, NY, USA, 433–436
Valentin Dallmeier and Thomas Zimmermann. 2007 · 2007
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GraphCodeBERT: Pre-training Code Representations with Data Flow
Daya Guo, Shuo Ren, Shuai Lu, Zhangyin Feng, Duyu Tang, Shujie Liu, Long Zhou, Nan Duan, Alexey Svyatkovskiy, Shengyu Fu, Michele Tufano, Shao Kun Deng, Colin Clement, Dawn Drain, Neel Sundaresan, Jian Yin, Daxin Jiang, and Ming Zhou. 2021 · 2009
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The probabilistic relevance framework: BM25 and beyond
Stephen Robertson, Hugo Zaragoza, et al · 2009
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GenProg: A Generic Method for Automatic Software Repair
Claire Le Goues, ThanhVu Nguyen, Stephanie Forrest, and Westley Weimer. 2012 · 2012
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Injecting mechanical faults to localize developer faults for evolving software
Lingming Zhang, Lu Zhang, and Sarfraz Khurshid. 2013 · 2013
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The Plastic Surgery Hypothesis. In Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (Hong Kong, China) (FSE 2014) . Association for Computing Machinery, New York, NY, USA, 306–317
Earl T. Barr, Yuriy Brun, Premkumar Devanbu, Mark Harman, and Federica Sarro. 2014 · 2014
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Automatic Repair of Buggy If Conditions and Missing Preconditions with SMT. In Proceedings of the 6th International Workshop on Constraints in Software Testing, Verification, and Analysis (Hyderabad, India) (CSTVA 2014) . 30–39
Favio DeMarco, Jifeng Xuan, Daniel Le Berre, and Martin Monperrus. 2014 · 2014
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Defects4J: A Database of Existing Faults to Enable Controlled Testing Studies for Java Programs (ISSTA 2014) . Association for Computing Machinery, New York, NY, USA, 437–440
René Just, Darioush Jalali, and Michael D. Ernst. 2014 · 2014
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Adam: A Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Ba. 2014 · 2014
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Sequence to Sequence Learning with Neural Networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014 · 2014
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Staged Program Repair with Condition Synthesis. In Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering (Bergamo, Italy) (ESEC/FSE 2015) . New York, NY, USA, 166–178
Fan Long and Martin Rinard. 2015 · 2015
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Automatic Repair of Real Bugs: An Experience Report on the Defects4J Dataset
Matias Martinez, Thomas Durieux, Jifeng Xuan, Romain Sommerard, and Martin Monperrus. 2015 · 2015
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Metallaxis-FL: mutation-based fault localization
Mike Papadakis and Yves Le Traon. 2015 · 2015
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An Analysis of Patch Plausibility and Correctness for Generate-and-Validate Patch Generation Systems. In Proceedings of the 2015 International Symposium on Software Testing and Analysis (Baltimore, MD, USA) (ISSTA 2015) . Association for Computing Machinery, New York, NY, USA, 24–36
Zichao Qi, Fan Long, Sara Achour, and Martin Rinard. 2015 · 2015
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History Driven Program Repair. In 2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER) , Vol. 1. 213–224
Xuan Bach D. Le, David Lo, and Claire Le Goues. 2016 · 2016
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Automatic Patch Generation by Learning Correct Code
Fan Long and Martin Rinard. 2016 · 2016
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ASTOR: A Program Repair Library for Java (Demo). In Proceedings of the 25th International Symposium on Software Testing and Analysis (Saarbrücken, Germany) (ISSTA 2016) . Association for Computing Machinery, New York, NY, USA, 441–444
Matias Martinez and Martin Monperrus. 2016 · 2016
Cited alongside, same era.
Angelix: Scalable Multiline Program Patch Synthesis via Symbolic Analysis. In Proceedings of the 38th International Conference on Software Engineering (Austin, Texas) (ICSE ’16) . 691–701
Sergey Mechtaev, Jooyong Yi, and Abhik Roychoudhury. 2016 · 2016
Cited alongside, same era.
A Survey on Software Fault Localization
W. Eric Wong, Ruizhi Gao, Yihao Li, Rui Abreu, and Franz Wotawa. 2016 · 2016
Cited alongside, same era.
Contract-based program repair without the contracts. In 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) . 637–647
Liushan Chen, Yu Pei, and Carlo A. Furia. 2017 · 2017
Cited alongside, same era.
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 (Virtual Event, USA) (ISSTA 2020) . Association for Computing Machinery, New York, NY, USA, 101–114
Thibaud Lutellier, Hung Viet Pham, Lawrence Pang, Yitong Li, Moshi Wei, and Lin Tan. 2020 · 2020
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Deep Learning for Software Defect Prediction: A Survey. In Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops (Seoul, Republic of Korea) (ICSEW’20) . Association for Computing Machinery, New York, NY, USA, 209–214
Safa Omri and Carsten Sinz. 2020 · 2020
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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Unified Pre-training for Program Understanding and Generation
Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, and Kai-Wei Chang. 2021 · 2021
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S3: syntax-and semantic-guided repair synthesis via programming by examples. In Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering . 593–604
Xuan-Bach D Le, Duc-Hiep Chu, David Lo, Claire Le Goues, and Willem Visser. 2017 · 2017
Cited alongside, same era.
Transforming programs and tests in tandem for fault localization
Xia Li and Lingming Zhang. 2017 · 2017
Cited alongside, same era.
Report: Software failure caused $1.7 trillion in financial losses in 2017
Scott Matteson. 2018 · 2017
Cited alongside, same era.
Elixir: Effective object-oriented program repair. In 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) . 648–659
Ripon K. Saha, Yingjun Lyu, Hiroaki Yoshida, and Mukul R. Prasad. 2017 · 2017
Cited alongside, same era.
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Cited alongside, same era.
SketchFix: A Tool for Automated Program Repair Approach Using Lazy Candidate Generation. In Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (Lake Buena Vista, FL, USA) (ESEC/FSE 2018) . ACM, 888–891
Jinru Hua, Mengshi Zhang, Kaiyuan Wang, and Sarfraz Khurshid. 2018 · 2018
Cited alongside, same era.
Shaping program repair space with existing patches and similar code. In Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2018, Amsterdam, The Netherlands, July 16-21, 2018 , Frank Tip and Eric Bodden (Eds.). ACM, 298–309
Jiajun Jiang, Yingfei Xiong, Hongyu Zhang, Qing Gao, and Xiangqun Chen. 2018 · 2018
Cited alongside, same era.
Later among the works it cites.
Program Synthesis with Large Language Models
Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, and Charles Sutton. 2021 · 2021
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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, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, and Wojciech Zaremba. 2021 · 2021
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CURE: Code-Aware Neural Machine Translation for Automatic Program Repair
Nan Jiang, Thibaud Lutellier, and Lin Tan. 2021 · 2021
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CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
Shuai Lu, Daya Guo, Shuo Ren, Junjie Huang, Alexey Svyatkovskiy, Ambrosio Blanco, Colin Clement, Dawn Drain, Daxin Jiang, Duyu Tang, Ge Li, Lidong Zhou, Linjun Shou, Long Zhou, Michele Tufano, Ming Gong, Ming Zhou, Nan Duan, Neel Sundaresan, Shao Kun Deng, Shengyu Fu, and Shujie Liu. 2021 · 2021
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CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021
Shafiq Joty Yue Wang, Weishi Wang and Steven C.H. Hoi. 2021 · 2021
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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 . ACM, New York, NY, USA, 341–353
Qihao Zhu, Zeyu Sun, Yuan-an Xiao, Wenjie Zhang, Kang Yuan, Yingfei Xiong, and Lu Zhang. 2021 · 2021
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PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, and Noah Fiedel. 2022 · 2022
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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
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Hugging Face
HuggingFace 2022 · 2022
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Patch Generation with Language Models: Feasibility and Scaling Behavior. In Deep Learning for Code Workshop
Sophia D Kolak, Ruben Martins, Claire Le Goues, and Vincent Josua Hellendoorn. 2022 · 2022
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Less is More: Summary of Long Instructions is Better for Program Synthesis
Kirby Kuznia, Swaroop Mishra, Mihir Parmar, and Chitta Baral. 2022 · 2022
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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
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Can OpenAI’s Codex Fix Bugs?: An evaluation on QuixBugs. In 2022 IEEE/ACM International Workshop on Automated Program Repair (APR) . 69–75
Julian Aron Prenner, Hlib Babii, and Romain Robbes. 2022 · 2022
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Natural language processing with transformers
Lewis Tunstall, Leandro von Werra, and Thomas Wolf. 2022 · 2022
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Bridging Pre-Trained Models and Downstream Tasks for Source Code Understanding. In Proceedings of the 44th International Conference on Software Engineering (Pittsburgh, Pennsylvania) (ICSE ’22) . Association for Computing Machinery, New York, NY, USA, 287–298
Deze Wang, Zhouyang Jia, Shanshan Li, Yue Yu, Yun Xiong, Wei Dong, and Xiangke Liao. 2022 · 2022
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Should You Mask 15% in Masked Language Modeling?
Alexander Wettig, Tianyu Gao, Zexuan Zhong, and Danqi Chen. 2022 · 2022
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Less Training, More Repairing Please: Revisiting Automated Program Repair via Zero-Shot Learning. In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2022)
Chunqiu Steven Xia and Lingming Zhang. 2022 · 2022
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A Systematic Evaluation of Large Language Models of Code. In Proceedings of the 6th ACM SIGPLAN International Symposium on Machine Programming (San Diego, CA, USA) (MAPS 2022) . Association for Computing Machinery, New York, NY, USA, 1–10
Frank F. Xu, Uri Alon, Graham Neubig, and Vincent Josua Hellendoorn. 2022 · 2022
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Neural Program Repair with Execution-based Backpropagation. In 2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) . 1506–1518
He Ye, Matias Martinez, and Martin Monperrus. 2022a · 2022
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JavaParser
JavaParser 2023 · 2023
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Automated Program Repair in the Era of Large Pre-trained Language Models. In Proceedings of the ACM/IEEE 45th International Conference on Software Engineering (ICSE ’23)
Chunqiu Steven Xia, Yuxiang Wei, and Lingming Zhang. 2023 · 2023
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FixMiner: Mining relevant fix patterns for automated program repair
Anil Koyuncu, Kui Liu, Tegawendé F. Bissyandé, Dongsun Kim, Jacques Klein, Martin Monperrus, and Yves Le Traon. 2020 · 2024
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