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Software development is a complex task that necessitates cooperation among multiple members with diverse skills.
Language Models are Few-Shot Learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D 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 Ziegler, Jeffrey Wu, Clemens Winter, Chris 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 · 1901
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Software Development: A Paradigm for The Future
Victor R Basili. 1989 · 1989
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Software Development Practices, Software Complexity, and Software Maintenance Performance: A Field Study
Rajiv D Banker, Gordon B Davis, and Sandra A Slaughter. 1998 · 1998
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Software development: Processes and Performance
Steve Sawyer and Patricia J. Guinan. 1998 · 1998
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Software Engineering Body of Knowledge (SWEBOK)
Peter Freeman, Donald J. Bagert, Hossein Saiedian, Mary Shaw, Robert Dupuis, and J. Barrie Thompson. 2001 · 2001
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Scaling Laws for Neural Language Models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001
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Emphasizing Human Capabilities in Software Development
Silvia T Acuna, Natalia Juristo, and Ana M Moreno. 2006 · 2006
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Large Language Models in Machine Translation
Thorsten Brants, Ashok C Popat, Peng Xu, Franz J Och, and Jeffrey Dean. 2007 · 2007
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Model-driven Development of Complex Software: A Research Roadmap
Robert France and Bernhard Rumpe. 2007 · 2007
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A Systematic Approach to the Comparison of Roles in the Software Development Processes
Murat Yilmaz, Rory V O’Connor, and Paul Clarke. 2012 · 2012
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Neural networks for predicting the duration of new software projects
Cuauhtémoc López Martín and Alain Abran. 2015 · 2015
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Automatically Learning Semantic Features for Defect Prediction
Song Wang, Taiyue Liu, and Lin Tan. 2016 · 2016
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Natural Language is a Programming Language: Applying Natural Language Processing to Software Development
Michael D. Ernst. 2017 · 2017
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Attention is All You Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Improving Automatic Source Code Summarization via Deep Reinforcement Learning
Yao Wan, Zhou Zhao, Min Yang, Guandong Xu, Haochao Ying, Jian Wu, and Philip S. Yu. 2018 · 2018
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A Neural Model for Method Name Generation from Functional Description
Sa Gao, Chunyang Chen, Zhenchang Xing, Yukun Ma, Wen Song, and Shang-Wei Lin. 2019 · 2019
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Extraction of System States from Natural Language Requirements
Florian Pudlitz, Florian Brokhausen, and Andreas Vogelsang. 2019 · 2019
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Feature Maps: A Comprehensible Software Representation for Design Pattern Detection
Hannes Thaller, Lukas Linsbauer, and Alexander Egyed. 2019 · 2019
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A Systematic Literature Survey of Software Metrics, Code Smells and Refactoring Techniques
Mansi Agnihotri and Anuradha Chug. 2020 · 2020
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Predicting How to Test Requirements: An Automated Approach
Jonas Winkler, Jannis Grönberg, and Andreas Vogelsang. 2020 · 2020
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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, et al. 2021 · 2021
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Automatic Unit Test Generation for Machine Learning Libraries: How Far Are We?
Song Wang, Nishtha Shrestha, Abarna Kucheri Subburaman, Junjie Wang, Moshi Wei, and Nachiappan Nagappan. 2021 · 2021
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War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars
Wenyue Hua, Lizhou Fan, Lingyao Li, Kai Mei, Jianchao Ji, Yingqiang Ge, Libby Hemphill, and Yongfeng Zhang. 2023 · 2023
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Survey of Hallucination in Natural Language Generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung. 2023 · 2023
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BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents
Zhiwei Liu, Weiran Yao, Jianguo Zhang, Le Xue, Shelby Heinecke, Rithesh Murthy, Yihao Feng, Zeyuan Chen, Juan Carlos Niebles, Devansh Arpit, Ran Xu, Phil Mui, Huan Wang, Caiming Xiong, and Silvio Savarese. 2023 · 2023
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Automated Handling of Anaphoric Ambiguity in Requirements: A Multi-solution Study
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Collaboration Challenges in Building ML-Enabled Systems: Communication, Documentation, Engineering, and Process
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Training Language Models to Follow Instructions with Human Feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
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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 Lundberg, Harsha Nori, Hamid Palangi, Marco Tulio Ribeiro, and Yi Zhang. 2023 · 2023
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ToolFormer: Language Models Can Teach Themselves to Use Tools
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ExpeL: LLM Agents Are Experiential Learners
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