| An empirical study on the usage of bert models for code completion M Ciniselli, N Cooper, L Pascarella, D Poshyvanyk, M Di Penta, G Bavota 2021 IEEE/ACM 18th International Conference on Mining Software Repositories …, 2021 | 46 | 2021 |
| 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 | 42 | 2021 |
| 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 | 25 | 2023 |
| To what extent do deep learning-based code recommenders generate predictions by cloning code from the training set? M Ciniselli, L Pascarella, G Bavota Proceedings of the 19th International Conference on Mining Software …, 2022 | 13 | 2022 |
| Source Code Recommender Systems: The Practitioners' Perspective M Ciniselli, L Pascarella, E Aghajani, S Scalabrino, R Oliveto, G Bavota arXiv preprint arXiv:2302.04098, 2023 | 1 | 2023 |
| Un approccio robusto per il problema dell'assegnamento ottimale dei pazienti agli operatori nei servizi di assistenza domiciliare M CINISELLI Italy, 2015 | | 2015 |
| 2021 IEEE/ACM 18th International Conference on Mining Software Repositories (MSR)| 978-1-7281-8710-5/20/$31.00© 2021 IEEE| DOI: 10.1109/MSR52588. 2021.00090 R Abdalkareem, S Afroz, D Aggarwal, E Aghajani, V Agrahari, ... | | |
