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Unit testing is an essential yet frequently arduous task.
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Randoop: feedback-directed random testing for Java. In Companion to the 22nd ACM SIGPLAN conference on Object-oriented programming systems and applications companion . 815–816
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Evosuite: automatic test suite generation for object-oriented software. In Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering . 416–419
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Unit test case generation with transformers and focal context
Michele Tufano, Dawn Drain, Alexey Svyatkovskiy, Shao Kun Deng, and Neel Sundaresan. 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
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Graph-based seed object synthesis for search-based unit testing. In Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering . 1068–1080
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Code llama: Open foundation models for code
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Adaptive test generation using a large language model
Max Schäfer, Sarah Nadi, Aryaz Eghbali, and Frank Tip. 2023 · 2023
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No More Manual Tests? Evaluating and Improving ChatGPT for Unit Test Generation
Zhiqiang Yuan, Yiling Lou, Mingwei Liu, Shiji Ding, Kaixin Wang, Yixuan Chen, and Xin Peng. 2023 · 2023
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Saranya Alagarsamy, Chakkrit Tantithamthavorn, and Aldeida Aleti. 2023 · 2023
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Lost in the middle: How language models use long contexts
Nelson F Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang. 2023 · 2023
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Generative Type Inference for Python
Yun Peng, Chaozheng Wang, Wenxuan Wang, Cuiyun Gao, and Michael R Lyu. 2023 · 2023
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CAT-LM training language models on aligned code and tests. In 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE) . IEEE, 409–420
Nikitha Rao, Kush Jain, Uri Alon, Claire Le Goues, and Vincent J Hellendoorn. 2023 · 2023
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https://github.com/ZJU-ACES-ISE/chatunitest-core
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CoverUp: Coverage-Guided LLM-Based Test Generation
Juan Altmayer Pizzorno and Emery D Berger. 2024 · 2024
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Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM
Gabriel Ryan, Siddhartha Jain, Mingyue Shang, Shiqi Wang, Xiaofei Ma, Murali Krishna Ramanathan, and Baishakhi Ray. 2024 · 2024
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Software testing with large language models: Survey, landscape, and vision
Junjie Wang, Yuchao Huang, Chunyang Chen, Zhe Liu, Song Wang, and Qing Wang. 2024 · 2024
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Enhancing LLM-based Test Generation for Hard-to-Cover Branches via Program Analysis
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