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In software maintenance, bug reproduction is essential for effective fault localization and repair.
Automatic Generation of Floating-Point Test Data
Webb Miller and David L. Spooner. 1976 · 1976
Earlier work this paper cites.
A study of effective regression testing in practice. In Eighth International Symposium on Software Reliability Engineering, ISSRE 1997, Albuquerque, NM, USA, November 2-5, 1997 . IEEE Computer Society, 264–274
W. Eric Wong, Joseph R. Horgan, Saul London, and Hiralal Agrawal. 1997 · 1997
Earlier work this paper cites.
Software Unit Test Coverage and Adequacy
Hong Zhu, Patrick A. V. Hall, and John H. R. May. 1997 · 1997
Earlier work this paper cites.
Unit testing: test early, test often
Michael Olan. 2003 · 2003
Earlier work this paper cites.
A Survey of Unit Testing Practices
Per Runeson. 2006 · 2006
Earlier work this paper cites.
Randoop: feedback-directed random testing for Java. In Companion to the 22nd Annual ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, OOPSLA 2007, October 21-25, 2007, Montreal, Quebec, Canada , Richard P. Gabriel, David F. Bacon, Cristina Videira Lopes, and Guy L. Steele Jr. (Eds.). ACM, 815–816
Carlos Pacheco and Michael D. Ernst. 2007 · 2007
Earlier work this paper cites.
The Probabilistic Relevance Framework: BM25 and Beyond
Stephen E. Robertson and Hugo Zaragoza. 2009 · 2009
Earlier work this paper cites.
Whole Test Suite Generation
Gordon Fraser and Andrea Arcuri. 2013 · 2012
Earlier work this paper cites.
A Survey on Unit Testing Practices and Problems. In 25th IEEE International Symposium on Software Reliability Engineering, ISSRE 2014, Naples, Italy, November 3-6, 2014 . IEEE Computer Society, 201–211
Ermira Daka and Gordon Fraser. 2014 · 2014
Earlier work this paper cites.
Information retrieval and spectrum based bug localization: better together. In Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, ESEC/FSE 2015, Bergamo, Italy, August 30 - September 4, 2015 , Elisabetta Di Nitto, Mark Harman, and Patrick Heymans (Eds.). ACM, 579–590
Tien-Duy B. Le, Richard Jayadi Oentaryo, and David Lo. 2015 · 2015
Earlier work this paper cites.
JCHARMING: A bug reproduction approach using crash traces and directed model checking. In 22nd IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2015, Montreal, QC, Canada, March 2-6, 2015 , Yann-Gaël Guéhéneuc, Bram Adams, and Alexander Serebrenik (Eds.). IEEE Computer Society, 101–110
Mathieu Nayrolles, Abdelwahab Hamou-Lhadj, Sofiène Tahar, and Alf Larsson. 2015 · 2015
Earlier work this paper cites.
Single-objective Versus Multi-objectivized Optimization for Evolutionary Crash Reproduction. In Search-Based Software Engineering - 10th International Symposium, SSBSE 2018, Montpellier, France, September 8-9, 2018, Proceedings (Lecture Notes in Computer Science, Vol. 11036) , Thelma Elita Colanzi and Phil McMinn (Eds.). Springer, 325–340
Mozhan Soltani, Pouria Derakhshanfar, Annibale Panichella, Xavier Devroey, Andy Zaidman, and Arie van Deursen. 2018 · 2018
Earlier work this paper cites.
Practitioners’ views on good software testing practices. In Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice, ICSE (SEIP) 2019, Montreal, QC, Canada, May 25-31, 2019 , Helen Sharp and Mike Whalen (Eds.). IEEE / ACM, 61–70
Pavneet Singh Kochhar, Xin Xia, and David Lo. 2019 · 2019
Earlier work this paper cites.
Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual , Hugo Larochelle, Marc’Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, and Hsuan-Tien Lin (Eds.)
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
Earlier work this paper cites.
Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm. In CHI ’21: CHI Conference on Human Factors in Computing Systems, Virtual Event / Yokohama Japan, May 8-13, 2021, Extended Abstracts , Yoshifumi Kitamura, Aaron Quigley, Katherine Isbister, and Takeo Igarashi (Eds.). ACM, 314:1–314:7
Laria Reynolds and Kyle McDonell. 2021 · 2021
Earlier work this paper cites.
Finite State Machines
John T. Taylor and Wayne T. Taylor. 2021 · 2021
Earlier work this paper cites.
Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs
Chetan Arora, John Grundy, and Mohamed Abdelrazek. 2023 · 2023
Earlier work this paper cites.
AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors in Agents
Weize Chen, Yusheng Su, Jingwei Zuo, Cheng Yang, Chenfei Yuan, Chen Qian, Chi-Min Chan, Yujia Qin, Yaxi Lu, Ruobing Xie, Zhiyuan Liu, Maosong Sun, and Jie Zhou. 2023 · 2023
Earlier work this paper cites.
PentestGPT: An LLM-empowered Automatic Penetration Testing Tool
Gelei Deng, Yi Liu, Victor Mayoral Vilches, Peng Liu, Yuekang Li, Yuan Xu, Tianwei Zhang, Yang Liu, Martin Pinzger, and Stefan Rass. 2023 · 2023
Earlier work this paper cites.
Gang Fan, Xiaoheng Xie, Xunjin Zheng, Yinan Liang, and Peng Di. 2023 · 2023
Cited alongside, same era.
AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation
Dong Huang, Qingwen Bu, Jie M. Zhang, Michael Luck, and Heming Cui. 2023 · 2023
Cited alongside, same era.
Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction. In 45th IEEE/ACM International Conference on Software Engineering, ICSE 2023, Melbourne, Australia, May 14-20, 2023 . IEEE, 2312–2323
Sungmin Kang, Juyeon Yoon, and Shin Yoo. 2023 · 2023
Cited alongside, same era.
OpenAI. 2023 · 2023
Cited alongside, same era.
Yoichi Ishibashi and Yoshimasa Nishimura. 2024 · 2024
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SWE-bench: Can Language Models Resolve Real-world Github Issues?. In The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024 . OpenReview.net
Carlos E. Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik R. Narasimhan. 2024 · 2024
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MARE: Multi-Agents Collaboration Framework for Requirements Engineering
Dongming Jin, Zhi Jin, Xiaohong Chen, and Chunhui Wang. 2024 · 2024
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MarsCode Agent: AI-native Automated Bug Fixing
Yizhou Liu, Pengfei Gao, Xinchen Wang, Chao Peng, and Zhao Zhang. 2024 · 2024
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requests
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