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Michele Tufano
Michele Tufano
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Graphcodebert: Pre-training code representations with data flow
D Guo, S Ren, S Lu, Z Feng, D Tang, S Liu, L Zhou, N Duan, ...
arXiv preprint arXiv:2009.08366, 2020
9762020
Codexglue: A machine learning benchmark dataset for code understanding and generation
S Lu, D Guo, S Ren, J Huang, A Svyatkovskiy, A Blanco, C Clement, ...
arXiv preprint arXiv:2102.04664, 2021
7962021
Deep learning code fragments for code clone detection
M White, M Tufano, C Vendome, D Poshyvanyk
Proceedings of the 31st IEEE/ACM international conference on automated …, 2016
7532016
SequenceR: Sequence-to-Sequence Learning for End-to-End Program Repair
Z Chen, S Kommrusch, M Tufano, LN Pouchet, D Poshyvanyk, ...
IEEE Transactions on Software Engineering 47 (9), 1943-1959, 2019
5302019
When and why your code starts to smell bad
M Tufano, F Palomba, G Bavota, R Oliveto, M Di Penta, A De Lucia, ...
2015 IEEE/ACM 37th IEEE International Conference on Software Engineering 1 …, 2015
3992015
An empirical study on learning bug-fixing patches in the wild via neural machine translation
M Tufano, C Watson, G Bavota, MD Penta, M White, D Poshyvanyk
ACM Transactions on Software Engineering and Methodology (TOSEM) 28 (4), 1-29, 2019
3812019
When and why your code starts to smell bad (and whether the smells go away)
M Tufano, F Palomba, G Bavota, R Oliveto, M Di Penta, A De Lucia, ...
IEEE Transactions on Software Engineering 43 (11), 1063-1088, 2017
2792017
On learning meaningful code changes via neural machine translation
M Tufano, J Pantiuchina, C Watson, G Bavota, D Poshyvanyk
2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE …, 2019
2572019
Sorting and transforming program repair ingredients via deep learning code similarities
M White, M Tufano, M Martinez, M Monperrus, D Poshyvanyk
2019 IEEE 26th international conference on software analysis, evolution and …, 2019
2122019
An empirical investigation into the nature of test smells
M Tufano, F Palomba, G Bavota, M Di Penta, R Oliveto, A De Lucia, ...
Proceedings of the 31st IEEE/ACM international conference on automated …, 2016
1862016
Deep learning similarities from different representations of source code
M Tufano, C Watson, G Bavota, M Di Penta, M White, D Poshyvanyk
Proceedings of the 15th international conference on mining software …, 2018
1852018
An empirical investigation into learning bug-fixing patches in the wild via neural machine translation
M Tufano, C Watson, G Bavota, M Di Penta, M White, D Poshyvanyk
Proceedings of the 33rd ACM/IEEE International Conference on Automated …, 2018
1692018
On learning meaningful assert statements for unit test cases
C Watson, M Tufano, K Moran, G Bavota, D Poshyvanyk
Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020
1512020
Inferfix: End-to-end program repair with llms
M Jin, S Shahriar, M Tufano, X Shi, S Lu, N Sundaresan, A Svyatkovskiy
Proceedings of the 31st ACM Joint European Software Engineering Conference …, 2023
1362023
Towards automating code review activities
R Tufano, L Pascarella, M Tufano, D Poshyvanyk, G Bavota
2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE …, 2021
1212021
There and back again: Can you compile that snapshot?
M Tufano, F Palomba, G Bavota, M Di Penta, R Oliveto, A De Lucia, ...
Journal of Software: Evolution and Process 29 (4), e1838, 2017
1212017
Enabling mutation testing for android apps
M Linares-Vásquez, G Bavota, M Tufano, K Moran, M Di Penta, ...
Proceedings of the 2017 11th Joint Meeting on Foundations of Software …, 2017
1022017
Landfill: An open dataset of code smells with public evaluation
F Palomba, D Di Nucci, M Tufano, G Bavota, R Oliveto, D Poshyvanyk, ...
2015 IEEE/ACM 12th Working Conference on Mining Software Repositories, 482-485, 2015
832015
Learning how to mutate source code from bug-fixes
M Tufano, C Watson, G Bavota, M Di Penta, M White, D Poshyvanyk
2019 IEEE International conference on software maintenance and evolution …, 2019
812019
Unit test case generation with transformers and focal context
M Tufano, D Drain, A Svyatkovskiy, SK Deng, N Sundaresan
arXiv preprint arXiv:2009.05617, 2020
602020
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