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In software development, resolving the emergent issues within GitHub repositories is a complex challenge that involves not only the incorporation of new code but also the maintenance of existing code.
Attribute grammars as a functional programming paradigm
Thomas Johnsson · 1987
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Okapi at TREC-3
Stephen E. Robertson, Steve Walker, Susan Jones, Micheline Hancock-Beaulieu, and Mike Gatford · 1994
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Where should the bugs be fixed? more accurate information retrieval-based bug localization based on bug reports
Jian Zhou, Hongyu Zhang, and David Lo · 2012
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Got issues? who cares about it? A large scale investigation of issue trackers from github
Tegawendé F. Bissyandé, David Lo, Lingxiao Jiang, Laurent Réveillère, Jacques Klein, and Yves Le Traon · 2013
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Impact of developer reputation on code review outcomes in OSS projects: an empirical investigation
Amiangshu Bosu and Jeffrey C. Carver · 2014
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The impact of code review coverage and code review participation on software quality: a case study of the qt, vtk, and ITK projects
Shane McIntosh, Yasutaka Kamei, Bram Adams, and Ahmed E. Hassan · 2014
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Investigating code review quality: Do people and participation matter?
Oleksii Kononenko, Olga Baysal, Latifa Guerrouj, Yaxin Cao, and Michael W. Godfrey · 2015
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Factors influencing code review processes in industry
Tobias Baum, Olga Liskin, Kai Niklas, and Kurt Schneider · 2016
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Multiple facets for dynamic information flow with exceptions
Thomas H. Austin, Thomas Schmitz, and Cormac Flanagan · 2017
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Improving language understanding by generative pre-training, 2018
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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Fault analysis and debugging of microservice systems: Industrial survey, benchmark system, and empirical study
Xiang Zhou, Xin Peng, Tao Xie, Jun Sun, Chao Ji, Wenhai Li, and Dan Ding · 2018
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Program synthesis with large language models
Jacob Austin, Augustus Odena, Maxwell I. Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie J. Cai, Michael Terry, Quoc V. Le, and Charles Sutton · 2021
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Pondé de Oliveira Pinto, Jared Kaplan, Harrison 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, Joshua 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
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Dreamloc: A deep relevance matching-based framework for bug localization
Binhang Qi, Hailong Sun, Wei Yuan, Hongyu Zhang, and Xiangxin Meng · 2021
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Codet5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation
Yue Wang, Weishi Wang, Shafiq R. Joty, and Steven C. H. Hoi · 2021
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Varfix: balancing edit expressiveness and search effectiveness in automated program repair
Chu-Pan Wong, Priscila Santiesteban, Christian Kästner, and Claire Le Goues · 2021
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Practitioners’ expectations on automated code comment generation
Xing Hu, Xin Xia, David Lo, Zhiyuan Wan, Qiuyuan Chen, and Thomas Zimmermann · 2022
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Claude 2
Anthropic · 2023
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Sparks of artificial general intelligence: Early experiments with GPT-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott M. Lundberg, Harsha Nori, Hamid Palangi, Marco Túlio Ribeiro, and Yi Zhang · 2023
Cited alongside, same era.
Chateval: Towards better llm-based evaluators through multi-agent debate
Chi-Min Chan, Weize Chen, Yusheng Su, Jianxuan Yu, Wei Xue, Shanghang Zhang, Jie Fu, and Zhiyuan Liu · 2023
Cited alongside, same era.
PTP: boosting stability and performance of prompt tuning with perturbation-based regularizer
Lichang Chen, Jiuhai Chen, Heng Huang, and Minhao Cheng · 2023
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Classeval: A manually-crafted benchmark for evaluating llms on class-level code generation, 2023
Xueying Du, Mingwei Liu, Kaixin Wang, Hanlin Wang, Junwei Liu, Yixuan Chen, Jiayi Feng, Chaofeng Sha, Xin Peng, and Yiling Lou · 2023
Cited alongside, same era.
Openllama: An open reproduction of llama, May 2023
A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, Yifan Li, Xinyu Tang, Zikang Liu, Peiyu Liu, Jian-Yun Nie, and Ji-Rong Wen · 2023
Later among the works it cites.
Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica · 2023
Later among the works it cites.
Thread of thought unraveling chaotic contexts
Yucheng Zhou, Xiubo Geng, Tao Shen, Chongyang Tao, Guodong Long, Jian-Guang Lou, and Jianbing Shen · 2023
Later among the works it cites.
Repairagent: An autonomous, llm-based agent for program repair
Islem Bouzenia, Premkumar T. Devanbu, and Michael Pradel · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Xinyang Geng and Hao Liu · 2023
Cited alongside, same era.
Metagpt: Meta programming for a multi-agent collaborative framework, 2023
Sirui Hong, Mingchen Zhuge, Jonathan Chen, Xiawu Zheng, Yuheng Cheng, Ceyao Zhang, Jinlin Wang, Zili Wang, Steven Ka Shing Yau, Zijuan Lin, Liyang Zhou, Chenyu Ran, Lingfeng Xiao, Chenglin Wu, and Jürgen Schmidhuber · 2023
Cited alongside, same era.
Large language models for software engineering: A systematic literature review
Xinyi Hou, Yanjie Zhao, Yue Liu, Zhou Yang, Kailong Wang, Li Li, Xiapu Luo, David Lo, John C. Grundy, and Haoyu Wang · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Developer-intent driven code comment generation
Fangwen Mu, Xiao Chen, Lin Shi, Song Wang, and Qing Wang · 2023
Cited alongside, same era.
OpenAI · 2023
Cited alongside, same era.
Communicative agents for software development
Chen Qian, Xin Cong, Wei Liu, Cheng Yang, Weize Chen, Yusheng Su, Yufan Dang, Jiahao Li, Juyuan Xu, Dahai Li, Zhiyuan Liu, and Maosong Sun · 2023
Cited alongside, same era.
Best practices for prompt engineering with openai api
Jessica Shieh · 2023
Cited alongside, same era.
Jiayi Geng Carlos E. Jimenez, John Yang · 2024
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Swe-bench_api_generation
Google Drive · 2024
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Data interpreter: An LLM agent for data science
Sirui Hong, Yizhang Lin, Bang Liu, Bangbang Liu, Binhao Wu, Danyang Li, Jiaqi Chen, Jiayi Zhang, Jinlin Wang, Li Zhang, Lingyao Zhang, Min Yang, Mingchen Zhuge, Taicheng Guo, Tuo Zhou, Wei Tao, Wenyi Wang, Xiangru Tang, Xiangtao Lu, Xiawu Zheng, Xinbing Liang, Yaying Fei, Yuheng Cheng, Zongze Xu, and Chenglin Wu · 2024
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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 · 2024
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Long-context llms struggle with long in-context learning
Tianle Li, Ge Zhang, Quy Duc Do, Xiang Yue, and Wenhu Chen · 2024
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OpenDevin: An Open Platform for AI Software Developers as Generalist Agents
OpenDevin Team · 2024
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A survey of neural code intelligence: Paradigms, advances and beyond, 2024
Qiushi Sun, Zhirui Chen, Fangzhi Xu, Kanzhi Cheng, Chang Ma, Zhangyue Yin, Jianing Wang, Chengcheng Han, Renyu Zhu, Shuai Yuan, Qipeng Guo, Xipeng Qiu, Pengcheng Yin, Xiaoli Li, Fei Yuan, Lingpeng Kong, Xiang Li, and Zhiyong Wu · 2024
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Kadel: Knowledge-aware denoising learning for commit message generation
Wei Tao, Yucheng Zhou, Yanlin Wang, Hongyu Zhang, Haofen Wang, and Wenqiang Zhang · 2024
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Swe-bench technical report, 2024
The Cognition Team · 2024
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Autodev: Automated ai-driven development, 2024
Michele Tufano, Anisha Agarwal, Jinu Jang, Roshanak Zilouchian Moghaddam, and Neel Sundaresan · 2024
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Swe-agent: Agent computer interfaces enable software engineering language models, 2024
John Yang, Carlos E. Jimenez, Alexander Wettig, Kilian Lieret, Shunyu Yao, Karthik Narasimhan, and Ofir Press · 2024
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ITER: iterative neural repair for multi-location patches
He Ye and Martin Monperrus · 2024
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Llama-moe: Building mixture-of-experts from llama with continual pre-training
Tong Zhu, Xiaoye Qu, Daize Dong, Jiacheng Ruan, Jingqi Tong, Conghui He, and Yu Cheng · 2024
Closest in time.