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Reproducing buggy code is the first and crucially important step in issue resolving, as it aids in identifying the underlying problems and validating that generated patches resolve the problem.
An integrated structure and scaling methodology for severe accident technical issue resolution: development of methodology
Novak Zuber, Gary E Wilson, Mamoru Ishii, Wolfgang Wulff, BE Boyack, AE Dukler, P Griffith, JM Healzer, RE Henry, JR Lehner, et al · 1998
Earlier work this paper cites.
On the accuracy of spectrum-based fault localization. In Testing: Academic and industrial conference practice and research techniques-MUTATION (TAICPART-MUTATION 2007) . IEEE, 89–98
Rui Abreu, Peter Zoeteweij, and Arjan JC Van Gemund. 2007 · 2007
Earlier work this paper cites.
A practical evaluation of spectrum-based fault localization
Rui Abreu, Peter Zoeteweij, Rob Golsteijn, and Arjan JC Van Gemund. 2009 · 2009
Earlier work this paper cites.
Accurate developer recommendation for bug resolution. In 2013 20th Working Conference on Reverse Engineering (WCRE) . IEEE, 72–81
Xin Xia, David Lo, Xinyu Wang, and Bo Zhou. 2013 · 2013
Earlier work this paper cites.
A literature review of research in bug resolution: Tasks, challenges and future directions
Tao Zhang, He Jiang, Xiapu Luo, and Alvin TS Chan. 2016 · 2016
Earlier work this paper 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, et al · 2021
Earlier work this paper cites.
On multi-modal learning of editing source code. In 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 443–455
Saikat Chakraborty and Baishakhi Ray. 2021 · 2021
Earlier work this paper cites.
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
Earlier work this paper cites.
Competition-level code generation with AlphaCode
Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d’Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, and Oriol Vinyals. 2022 · 2022
Earlier work this paper cites.
React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2022 · 2022
Earlier work this paper cites.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Earlier work this paper cites.
Teaching large language models to self-debug
Xinyun Chen, Maxwell Lin, Nathanael Schärli, and Denny Zhou. 2023 · 2023
Earlier work this paper cites.
Introducing Devin
Cognition. 2023 · 2023
Earlier work this paper cites.
Towards Better Multilingual Code Search through Cross-Lingual Contrastive Learning. In Proceedings of the 14th Asia-Pacific Symposium on Internetware . 22–32
Xiangbing Huang, Yingwei Ma, Haifang Zhou, Zhijie Jiang, Yuanliang Zhang, Teng Wang, and Shanshan Li. 2023 · 2023
Earlier work this paper cites.
Automatic Code Annotation Generation Based on Heterogeneous Graph Structure. In 2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) . IEEE, 497–508
Zhijie Jiang, Haixu Xiong, Yingwei Ma, Yao Zhang, Yan Ding, Yun Xiong, and Shanshan Li. 2023 · 2023
Earlier work this paper cites.
Swe-bench: Can language models resolve real-world github issues?
Carlos E Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik Narasimhan. 2023 · 2023
Earlier work this paper cites.
Large language models are few-shot testers: Exploring llm-based general bug reproduction. In 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE) . IEEE, 2312–2323
Sungmin Kang, Juyeon Yoon, and Shin Yoo. 2023 · 2023
Earlier work this paper cites.
A two-stage framework for ambiguous classification in software engineering. In 2023 IEEE 34th International Symposium on Software Reliability Engineering (ISSRE) . IEEE, 275–286
Jiaying Li, Yan Lei, Shanshan Li, Haifang Zhou, Yue Yu, Zhouyang Jia, Yingwei Ma, and Teng Wang. 2023a · 2023
Cited alongside, same era.
Codeeditor: Learning to edit source code with pre-trained models
Jia Li, Ge Li, Zhuo Li, Zhi Jin, Xing Hu, Kechi Zhang, and Zhiyi Fu. 2023b · 2023
Cited alongside, same era.
Wizardcoder: Empowering code large language models with evol-instruct
Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, Qingwei Lin, and Daxin Jiang. 2023 · 2023
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At Which Training Stage Does Code Data Help LLMs Reasoning?
Yingwei Ma, Yue Liu, Yue Yu, Yuanliang Zhang, Yu Jiang, Changjian Wang, and Shanshan Li. 2023a · 2023
Cited alongside, same era.
MarsCode Agent: AI-native Automated Bug Fixing
Yizhou Liu, Pengfei Gao, Xinchen Wang, Chao Peng, and Zhao Zhang. 2024b · 2024
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Yingwei Ma, Rongyu Cao, Yongchang Cao, Yue Zhang, Jue Chen, Yibo Liu, Yuchen Liu, Binhua Li, Fei Huang, and Yongbin Li. 2024a · 2024
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How to Understand Whole Software Repository?
Yingwei Ma, Qingping Yang, Rongyu Cao, Binhua Li, Fei Huang, and Yongbin Li. 2024b · 2024
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Code Agents are State of the Art Software Testers
Niels Mündler, Mark Niklas Müller, Jingxuan He, and Martin Vechev. 2024 · 2024
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NExT: Teaching Large Language Models to Reason about Code Execution
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Mulcs: Towards a unified deep representation for multilingual code search. In 2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) . IEEE, 120–131
Yingwei Ma, Yue Yu, Shanshan Li, Zhouyang Jia, Jun Ma, Rulin Xu, Wei Dong, and Xiangke Liao. 2023b · 2023
Cited alongside, same era.
Understanding the effectiveness of large language models in code translation
Rangeet Pan, Ali Reza Ibrahimzada, Rahul Krishna, Divya Sankar, Lambert Pouguem Wassi, Michele Merler, Boris Sobolev, Raju Pavuluri, Saurabh Sinha, and Reyhaneh Jabbarvand. 2023 · 2023
Cited alongside, same era.
Refactoring programs using large language models with few-shot examples. In 2023 30th Asia-Pacific Software Engineering Conference (APSEC) . IEEE, 151–160
Atsushi Shirafuji, Yusuke Oda, Jun Suzuki, Makoto Morishita, and Yutaka Watanobe. 2023 · 2023
Cited alongside, same era.
Wavecoder: Widespread and versatile enhanced instruction tuning with refined data generation
Zhaojian Yu, Xin Zhang, Ning Shang, Yangyu Huang, Can Xu, Yishujie Zhao, Wenxiang Hu, and Qiufeng Yin. 2023 · 2023
Cited alongside, same era.
Lampr: Boosting the Effectiveness of Language-Generic Program Reduction via Large Language Models
Mengxiao Zhang, Yongqiang Tian, Zhenyang Xu, Yiwen Dong, Shin Hwei Tan, and Chengnian Sun. 2023 · 2023
Cited alongside, same era.
How to refactor this code? An exploratory study on developer-ChatGPT refactoring conversations. In Proceedings of the 21st International Conference on Mining Software Repositories . 202–206
Eman Abdullah AlOmar, Anushkrishna Venkatakrishnan, Mohamed Wiem Mkaouer, Christian Newman, and Ali Ouni. 2024 · 2024
Cited alongside, same era.
SWE-bench Lite: A Canonical Subset for Efficient Evaluation of Language Models as Software Engineers
Carlos E. Jimenez, John Yang, Jiayi Geng. 2024 · 2024
Cited alongside, same era.
CodeR: Issue Resolving with Multi-Agent and Task Graphs
Dong Chen, Shaoxin Lin, Muhan Zeng, Daoguang Zan, Jian-Gang Wang, Anton Cheshkov, Jun Sun, Hao Yu, Guoliang Dong, Artem Aliev, et al · 2024
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Ansong Ni, Miltiadis Allamanis, Arman Cohan, Yinlin Deng, Kensen Shi, Charles Sutton, and Pengcheng Yin. 2024 · 2024
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Introducing GPT-4o
OpenAI. 2024 · 2024
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Codev-Bench: How Do LLMs Understand Developer-Centric Code Completion?
Zhenyu Pan, Rongyu Cao, Yongchang Cao, Yingwei Ma, Binhua Li, Fei Huang, Han Liu, and Yongbin Li. 2024 · 2024
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From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Yuling Shi, Songsong Wang, Chengcheng Wan, and Xiaodong Gu. 2024 · 2024
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In-Memory Learning: A Declarative Learning Framework for Large Language Models
Bo Wang, Tianxiang Sun, Hang Yan, Siyin Wang, Qingyuan Cheng, and Xipeng Qiu. 2024b · 2024
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Magicoder: Empowering code generation with oss-instruct. In Forty-first International Conference on Machine Learning
Yuxiang Wei, Zhe Wang, Jiawei Liu, Yifeng Ding, and Lingming Zhang. 2024 · 2024
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Agentless: Demystifying llm-based software engineering agents
Chunqiu Steven Xia, Yinlin Deng, Soren Dunn, and Lingming Zhang. 2024 · 2024
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CRUXEval-X: A Benchmark for Multilingual Code Reasoning, Understanding and Execution
Ruiyang Xu, Jialun Cao, Yaojie Lu, Hongyu Lin, Xianpei Han, Ben He, Shing-Chi Cheung, and Le Sun. 2024 · 2024
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Better Debugging: Combining Static Analysis and LLMs for Explainable Crashing Fault Localization
Jiwei Yan, Jinhao Huang, Chunrong Fang, Jun Yan, and Jian Zhang. 2024 · 2024
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Swe-agent: Agent-computer interfaces enable automated software engineering
John Yang, Carlos E Jimenez, Alexander Wettig, Kilian Lieret, Shunyu Yao, Karthik Narasimhan, and Ofir Press. 2024 · 2024
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DOMAINEVAL: An Auto-Constructed Benchmark for Multi-Domain Code Generation
Qiming Zhu, Jialun Cao, Yaojie Lu, Hongyu Lin, Xianpei Han, Le Sun, and Shing-Chi Cheung. 2024a · 2024
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DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence
Qihao Zhu, Daya Guo, Zhihong Shao, Dejian Yang, Peiyi Wang, Runxin Xu, Y Wu, Yukun Li, Huazuo Gao, Shirong Ma, et al · 2024
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