| On the robustness of code generation techniques: An empirical study on github copilot A Mastropaolo, L Pascarella, E Guglielmi, M Ciniselli, S Scalabrino, ... 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE …, 2023 | 92 | 2023 |
| 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 | 87 | 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 | 85 | 2021 |
| 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 | 24 | 2022 |
| Source code recommender systems: The practitioners' perspective M Ciniselli, L Pascarella, E Aghajani, S Scalabrino, R Oliveto, G Bavota 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE …, 2023 | 13 | 2023 |
| Evaluating Code Summarization Techniques: A New Metric and an Empirical Characterization A Mastropaolo, M Ciniselli, M Di Penta, G Bavota Proceedings of the IEEE/ACM 46th International Conference on Software …, 2024 | 10 | 2024 |
| Code review automation: strengths and weaknesses of the state of the art R Tufano, O Dabić, A Mastropaolo, M Ciniselli, G Bavota IEEE Transactions on Software Engineering, 2024 | 10 | 2024 |
| An Empirical Study on the Usage of BERT Models for Code Completion CoRR, vol. abs/2103.07115 (2021) M Ciniselli, N Cooper, L Pascarella, D Poshyvanyk, M Di Penta, G Bavota | 6 | |
| Towards Summarizing Code Snippets Using Pre-Trained Transformers A Mastropaolo, M Ciniselli, L Pascarella, R Tufano, E Aghajani, G Bavota Proceedings of the 32nd IEEE/ACM International Conference on Program …, 2024 | 3 | 2024 |
| The Trailer of the ACM 2030 Roadmap for Software Engineering M Pezzè, M Ciniselli, L Di Grazia, N Puccinelli, K Qiu ACM SIGSOFT Software Engineering Notes 49 (4), 31-40, 2024 | 2 | 2024 |
| From Today's Code to Tomorrow's Symphony: The AI Transformation of Developer's Routine by 2030 K Qiu, N Puccinelli, M Ciniselli, L Di Grazia arXiv preprint arXiv:2405.12731, 2024 | 2 | 2024 |
| On the Generalizability of Deep Learning-based Code Completion Across Programming Language Versions M Ciniselli, A Martin-Lopez, G Bavota Proceedings of the 32nd IEEE/ACM International Conference on Program …, 2024 | 1 | 2024 |
| Studying strengths and weaknesses of code recommenders M Ciniselli | | 2023 |
| Un approccio robusto per il problema dell'assegnamento ottimale dei pazienti agli operatori nei servizi di assistenza domiciliare M CINISELLI Politecnico di Milano, 2013 | | 2013 |
| 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, ... | | |
