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Michele Tufano

CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation


Feb 09, 2021
Shuai Lu, Daya Guo, Shuo Ren, Junjie Huang, Alexey Svyatkovskiy, Ambrosio Blanco, Colin Clement, Dawn Drain, Daxin Jiang, Duyu Tang, Ge Li, Lidong Zhou, Linjun Shou, Long Zhou, Michele Tufano, Ming Gong, Ming Zhou, Nan Duan, Neel Sundaresan, Shao Kun Deng, Shengyu Fu, Shujie Liu

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GraphCodeBERT: Pre-training Code Representations with Data Flow


Sep 29, 2020
Daya Guo, Shuo Ren, Shuai Lu, Zhangyin Feng, Duyu Tang, Shujie Liu, Long Zhou, Nan Duan, Alexey Svyatkovskiy, Shengyu Fu, Michele Tufano, Shao Kun Deng, Colin Clement, Dawn Drain, Neel Sundaresan, Jian Yin, Daxin Jiang, Ming Zhou

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Generating Accurate Assert Statements for Unit Test Cases using Pretrained Transformers


Sep 11, 2020
Michele Tufano, Dawn Drain, Alexey Svyatkovskiy, Neel Sundaresan

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Unit Test Case Generation with Transformers


Sep 11, 2020
Michele Tufano, Dawn Drain, Alexey Svyatkovskiy, Shao Kun Deng, Neel Sundaresan

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DeepMutation: A Neural Mutation Tool


Feb 13, 2020
Michele Tufano, Jason Kimko, Shiya Wang, Cody Watson, Gabriele Bavota, Massimiliano Di Penta, Denys Poshyvanyk

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* Accepted to the 42nd ACM/IEEE International Conference on Software Engineering (ICSE 2020), Demonstrations Track - Seoul, South Korea, May 23-29, 2020, 4 pages 
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On Learning Meaningful Code Changes via Neural Machine Translation


Jan 25, 2019
Michele Tufano, Jevgenija Pantiuchina, Cody Watson, Gabriele Bavota, Denys Poshyvanyk

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* Accepted to the 41st ACM/IEEE International Conference on Software Engineering (ICSE 2019) - Montreal, QC, Canada, May 25-31, 2019, 12 pages 
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SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair


Dec 24, 2018
Zimin Chen, Steve Kommrusch, Michele Tufano, Louis-Noël Pouchet, Denys Poshyvanyk, Martin Monperrus

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* 21 pages, 15 figures 
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