| Studying the usage of text-to-text transfer transformer to support code-related tasks A Mastropaolo, S Scalabrino, N Cooper, DN Palacio, D Poshyvanyk, ... 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE …, 2021 | 115 | 2021 |
| Using pre-trained models to boost code review automation R Tufano, S Masiero, A Mastropaolo, L Pascarella, D Poshyvanyk, ... Proceedings of the 44th International Conference on Software Engineering …, 2022 | 38 | 2022 |
| An empirical study on the usage of transformer models for code completion M Ciniselli, N Cooper, L Pascarella, A Mastropaolo, E Aghajani, ... IEEE Transactions on Software Engineering 48 (12), 4818-4837, 2021 | 36 | 2021 |
| Using transfer learning for code-related tasks A Mastropaolo, N Cooper, DN Palacio, S Scalabrino, D Poshyvanyk, ... IEEE Transactions on Software Engineering 49 (4), 1580-1598, 2022 | 25 | 2022 |
| Using deep learning to generate complete log statements A Mastropaolo, L Pascarella, G Bavota Proceedings of the 44th International Conference on Software Engineering …, 2022 | 19 | 2022 |
| On the robustness of code generation techniques: An empirical study on github copilot A Mastropaolo, L Pascarella, E Guglielmi, M Ciniselli, S Scalabrino, ... arXiv preprint arXiv:2302.00438, 2023 | 17 | 2023 |
| An empirical study on code comment completion A Mastropaolo, E Aghajani, L Pascarella, G Bavota 2021 IEEE International Conference on Software Maintenance and Evolution …, 2021 | 12 | 2021 |
| An adaptive search budget allocation approach for search-based test case generation S Scalabrino, A Mastropaolo, G Bavota, R Oliveto ACM Transactions on Software Engineering and Methodology (TOSEM) 30 (3), 1-26, 2021 | 3 | 2021 |
| Automated variable renaming: are we there yet? A Mastropaolo, E Aghajani, L Pascarella, G Bavota Empirical Software Engineering 28 (2), 45, 2023 | 2 | 2023 |
| Toward Automatically Completing GitHub Workflows A Mastropaolo, F Zampetti, M Di Penta, G Bavota arXiv preprint arXiv:2308.16774, 2023 | | 2023 |
| Towards Automatically Addressing Self-Admitted Technical Debt: How Far Are We? A Mastropaolo, M Di Penta, G Bavota arXiv preprint arXiv:2308.08943, 2023 | | 2023 |
| Automatically Generating Dockerfiles via Deep Learning: Challenges and Promises G Rosa, A Mastropaolo, S Scalabrino, G Bavota, R Oliveto arXiv preprint arXiv:2303.15990, 2023 | | 2023 |
Gabriele BavotaAssociate Professor, Università della Svizzera italiana (USI)Verified email at usi.ch
