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Antonio Mastropaolo
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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
2422021
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
1382022
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
832023
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
792021
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
602022
Using deep learning to generate complete log statements
A Mastropaolo, L Pascarella, G Bavota
Proceedings of the 44th International Conference on Software Engineering …, 2022
482022
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
202021
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
92024
Automated variable renaming: are we there yet?
A Mastropaolo, E Aghajani, L Pascarella, G Bavota
Empirical Software Engineering 28 (2), 45, 2023
92023
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
82024
How do Hugging Face Models Document Datasets, Bias, and Licenses? An Empirical Study
F Pepe, V Nardone, A Mastropaolo, G Bavota, G Canfora, M Di Penta
Proceedings of the 32nd IEEE/ACM International Conference on Program …, 2024
62024
Towards Automatically Addressing Self-Admitted Technical Debt: How Far Are We?
A Mastropaolo, M Di Penta, G Bavota
2023 38th IEEE/ACM International Conference on Automated Software …, 2023
52023
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
52021
Unveiling ChatGPT¢s Usage in Open Source Projects: A Mining-based Study
R Tufano, A Mastropaolo, F Pepe, O Dabić, M Di Penta, G Bavota
2024 IEEE/ACM 21st International Conference on Mining Software Repositories …, 2024
42024
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
22024
Log statements generation via deep learning: Widening the support provided to developers
A Mastropaolo, V Ferrari, L Pascarella, G Bavota
Journal of Systems and Software 210, 111947, 2024
22024
Toward Automatically Completing GitHub Workflows
A Mastropaolo, F Zampetti, M Di Penta, G Bavota
2024 IEEE/ACM 46th International Conference on Software Engineering (ICSE …, 2023
22023
The Rise and Fall (?) of Software Engineering
A Mastropaolo, C Escobar-Velásquez, M Linares-Vásquez
arXiv preprint arXiv:2406.10141, 2024
12024
A Taxonomy of Self-Admitted Technical Debt in Deep Learning Systems
F Pepe, F Zampetti, A Mastropaolo, G Bavota, M Di Penta
arXiv preprint arXiv:2409.11826, 2024
2024
How the Training Procedure Impacts the Performance of Deep Learning-based Vulnerability Patching
A Mastropaolo, V Nardone, G Bavota, M Di Penta
arXiv preprint arXiv:2404.17896, 2024
2024
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