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Software process models are essential to facilitate collaboration and communication among software teams to solve complex development tasks.
Assessing test-driven development at ibm
E Michael Maximilien and Laurie Williams · 2003
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Automatic detection and masking of nonatomic exception handling
Christof Fetzer, Pascal Felber, and Karin Hogstedt · 2004
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The new methodology, 2005
Martin Fowler · 2005
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Built-in exceptions, 2005
Python · 2005
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A simulation model for the waterfall software development life cycle
Youssef Bassil · 2012
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Do code smells reflect important maintainability aspects?
Aiko Yamashita and Leon Moonen · 2012
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Code quality: Examining the efficacy of automated tools
Subhasish Dasgupta and Sara Hooshangi · 2017
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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
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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
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Reordering examples helps during priming-based few-shot learning
Sawan Kumar and Partha Talukdar · 2021
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
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Alleviating the sample selection bias in few-shot learning by removing projection to the centroid
Jing Xu, Xu Luo, Xinglin Pan, Yanan Li, Wenjie Pei, and Zenglin Xu · 2022
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Metagpt: Meta programming for multi-agent collaborative framework
Sirui Hong, Xiawu Zheng, Jonathan Chen, Yuheng Cheng, Jinlin Wang, Ceyao Zhang, Zili Wang, Steven Ka Shing Yau, Zijuan Lin, Liyang Zhou, et al · 2023
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Large language models are few-shot testers: Exploring llm-based general bug reproduction
Sungmin Kang, Juyeon Yoon, and Shin Yoo · 2023
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Log parsing with prompt-based few-shot learning
Van-Hoang Le and Hongyu Zhang · 2023
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Structured chain-of-thought prompting for code generation
Jia Li, Ge Li, Yongmin Li, and Zhi Jin · 2023
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Retrieval-based prompt selection for code-related few-shot learning
Noor Nashid, Mifta Sintaha, and Ali Mesbah · 2023
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Generative agents: Interactive simulacra of human behavior
Joon Sung Park, Joseph O’Brien, Carrie Jun Cai, Meredith Ringel Morris, Percy Liang, and Michael S Bernstein · 2023
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Exploring large language models for communication games: An empirical study on werewolf
Yuzhuang Xu, Shuo Wang, Peng Li, Fuwen Luo, Xiaolong Wang, Weidong Liu, and Yang Liu · 2023
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Auto-gpt for online decision making: Benchmarks and additional opinions
Hui Yang, Sifu Yue, and Yunzhong He · 2023
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Burak Yetiştiren, Işık Özsoy, Miray Ayerdem, and Eray Tüzün · 2023
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Language agent tree search unifies reasoning acting and planning in language models
Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, and Yu-Xiong Wang · 2023
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Chen Qian, Xin Cong, Cheng Yang, Weize Chen, Yusheng Su, Juyuan Xu, Zhiyuan Liu, and Maosong Sun · 2023
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An empirical evaluation of using large language models for automated unit test generation
Max Schäfer, Sarah Nadi, Aryaz Eghbali, and Frank Tip · 2023
Cited alongside, same era.
Character-llm: A trainable agent for role-playing
Yunfan Shao, Linyang Li, Junqi Dai, and Xipeng Qiu · 2023
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Git merge conflict resolution leveraging strategy classification and llm
Chaochao Shen, Wenhua Yang, Minxue Pan, and Yu Zhou · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
Cited alongside, same era.
Jules White, Sam Hays, Quchen Fu, Jesse Spencer-Smith, and Douglas C Schmidt · 2023
Cited alongside, same era.
The rise and potential of large language model based agents: A survey
Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, et al · 2023
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Eman Abdullah AlOmar, Anushkrishna Venkatakrishnan, Mohamed Wiem Mkaouer, Christian D Newman, and Ali Ouni · 2024
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Repository & dataset, 2024
Anonymous · 2024
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Llmparser: An exploratory study on using large language models for log parsing
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Self-refine: Iterative refinement with self-feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, et al · 2024
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Fernando Vallecillos Ruiz, Anastasiia Grishina, Max Hort, and Leon Moonen · 2024
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Reflexion: Language agents with verbal reinforcement learning
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What is devtestops?
Testsigma · 2024
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Automatic commit message generation: A critical review and directions for future work
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Ldb: A large language model debugger via verifying runtime execution step-by-step
Li Zhong, Zilong Wang, and Jingbo Shang · 2024
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