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Matteo Ciniselli
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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
602021
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
582021
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
462023
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
192022
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
82023
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
12024
On the Generalizability of Deep Learning-based Code Completion Across Programming Language Versions
M Ciniselli, A Martin-Lopez, G Bavota
arXiv preprint arXiv:2403.15149, 2024
2024
Towards Summarizing Code Snippets Using Pre-Trained Transformers
A Mastropaolo, M Ciniselli, L Pascarella, R Tufano, E Aghajani, G Bavota
arXiv preprint arXiv:2402.00519, 2024
2024
Evaluating Code Summarization Techniques: A New Metric and an Empirical Characterization
A Mastropaolo, M Ciniselli, M Di Penta, G Bavota
2024
Evaluating Code Summarization Techniques: A New Metric and an Empirical Characterization
A Mastropaolo, M Ciniselli, M Di Penta, G Bavota
arXiv e-prints, arXiv: 2312.15475, 2023
2023
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, ...
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