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Antonio Mastropaolo
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2020 – today
- 2024
- [j6]Antonio Mastropaolo, Valentina Ferrari, Luca Pascarella, Gabriele Bavota:
Log statements generation via deep learning: Widening the support provided to developers. J. Syst. Softw. 210: 111947 (2024) - [j5]Rosalia Tufano, Ozren Dabic, Antonio Mastropaolo, Matteo Ciniselli, Gabriele Bavota:
Code Review Automation: Strengths and Weaknesses of the State of the Art. IEEE Trans. Software Eng. 50(2): 338-353 (2024) - [c14]Antonio Mastropaolo, Vittoria Nardone, Gabriele Bavota, Massimiliano Di Penta:
How the Training Procedure Impacts the Performance of Deep Learning-based Vulnerability Patching. EASE 2024: 150-159 - [c13]Antonio Mastropaolo, Fiorella Zampetti, Gabriele Bavota, Massimiliano Di Penta:
Toward Automatically Completing GitHub Workflows. ICSE 2024: 13:1-13:12 - [c12]Antonio Mastropaolo, Matteo Ciniselli, Massimiliano Di Penta, Gabriele Bavota:
Evaluating Code Summarization Techniques: A New Metric and an Empirical Characterization. ICSE 2024: 218:1-218:13 - [c11]Antonio Mastropaolo, Matteo Ciniselli, Luca Pascarella, Rosalia Tufano, Emad Aghajani, Gabriele Bavota:
Towards Summarizing Code Snippets Using Pre-Trained Transformers. ICPC 2024: 1-12 - [c10]Federica Pepe, Vittoria Nardone, Antonio Mastropaolo, Gabriele Bavota, Gerardo Canfora, Massimiliano Di Penta:
How do Hugging Face Models Document Datasets, Bias, and Licenses? An Empirical Study. ICPC 2024: 370-381 - [c9]Rosalia Tufano, Antonio Mastropaolo, Federica Pepe, Ozren Dabic, Massimiliano Di Penta, Gabriele Bavota:
Unveiling ChatGPT's Usage in Open Source Projects: A Mining-based Study. MSR 2024: 571-583 - [i19]Rosalia Tufano, Ozren Dabic, Antonio Mastropaolo, Matteo Ciniselli, Gabriele Bavota:
Code Review Automation: Strengths and Weaknesses of the State of the Art. CoRR abs/2401.05136 (2024) - [i18]Antonio Mastropaolo, Matteo Ciniselli, Luca Pascarella, Rosalia Tufano, Emad Aghajani, Gabriele Bavota:
Towards Summarizing Code Snippets Using Pre-Trained Transformers. CoRR abs/2402.00519 (2024) - [i17]Rosalia Tufano, Antonio Mastropaolo, Federica Pepe, Ozren Dabic, Massimiliano Di Penta, Gabriele Bavota:
Unveiling ChatGPT's Usage in Open Source Projects: A Mining-based Study. CoRR abs/2402.16480 (2024) - [i16]Antonio Mastropaolo, Vittoria Nardone, Gabriele Bavota, Massimiliano Di Penta:
How the Training Procedure Impacts the Performance of Deep Learning-based Vulnerability Patching. CoRR abs/2404.17896 (2024) - [i15]Antonio Mastropaolo, Camilo Escobar-Velásquez, Mario Linares-Vásquez:
The Rise and Fall(?) of Software Engineering. CoRR abs/2406.10141 (2024) - [i14]Federica Pepe, Fiorella Zampetti, Antonio Mastropaolo, Gabriele Bavota, Massimiliano Di Penta:
A Taxonomy of Self-Admitted Technical Debt in Deep Learning Systems. CoRR abs/2409.11826 (2024) - 2023
- [j4]Antonio Mastropaolo, Emad Aghajani, Luca Pascarella, Gabriele Bavota:
Automated variable renaming: are we there yet? Empir. Softw. Eng. 28(2): 45 (2023) - [j3]Antonio Mastropaolo, Nathan Cooper, David Nader-Palacio, Simone Scalabrino, Denys Poshyvanyk, Rocco Oliveto, Gabriele Bavota:
Using Transfer Learning for Code-Related Tasks. IEEE Trans. Software Eng. 49(4): 1580-1598 (2023) - [c8]Antonio Mastropaolo, Luca Pascarella, Emanuela Guglielmi, Matteo Ciniselli, Simone Scalabrino, Rocco Oliveto, Gabriele Bavota:
On the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot. ICSE 2023: 2149-2160 - [c7]Giovanni Rosa, Antonio Mastropaolo, Simone Scalabrino, Gabriele Bavota, Rocco Oliveto:
Automatically Generating Dockerfiles via Deep Learning: Challenges and Promises. ICSSP 2023: 1-12 - [c6]Antonio Mastropaolo, Massimiliano Di Penta, Gabriele Bavota:
Towards Automatically Addressing Self-Admitted Technical Debt: How Far Are We? ASE 2023: 585-597 - [d5]Federica Pepe, Vittoria Nardone, Antonio Mastropaolo, Gerardo Canfora, Gabriele Bavota, Massimiliano Di Penta:
Dataset of the paper: "How do Hugging Face Models Document Datasets, Bias, and Licenses? An Empirical Study". Zenodo, 2023 - [i13]Antonio Mastropaolo, Luca Pascarella, Emanuela Guglielmi, Matteo Ciniselli, Simone Scalabrino, Rocco Oliveto, Gabriele Bavota:
On the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot. CoRR abs/2302.00438 (2023) - [i12]Giovanni Rosa, Antonio Mastropaolo, Simone Scalabrino, Gabriele Bavota, Rocco Oliveto:
Automatically Generating Dockerfiles via Deep Learning: Challenges and Promises. CoRR abs/2303.15990 (2023) - [i11]Antonio Mastropaolo, Massimiliano Di Penta, Gabriele Bavota:
Towards Automatically Addressing Self-Admitted Technical Debt: How Far Are We? CoRR abs/2308.08943 (2023) - [i10]Antonio Mastropaolo, Fiorella Zampetti, Massimiliano Di Penta, Gabriele Bavota:
Toward Automatically Completing GitHub Workflows. CoRR abs/2308.16774 (2023) - [i9]Antonio Mastropaolo, Valentina Ferrari, Luca Pascarella, Gabriele Bavota:
Log Statements Generation via Deep Learning: Widening the Support Provided to Developers. CoRR abs/2311.04587 (2023) - [i8]Antonio Mastropaolo, Matteo Ciniselli, Massimiliano Di Penta, Gabriele Bavota:
Evaluating Code Summarization Techniques: A New Metric and an Empirical Characterization. CoRR abs/2312.15475 (2023) - 2022
- [j2]Matteo Ciniselli, Nathan Cooper, Luca Pascarella, Antonio Mastropaolo, Emad Aghajani, Denys Poshyvanyk, Massimiliano Di Penta, Gabriele Bavota:
An Empirical Study on the Usage of Transformer Models for Code Completion. IEEE Trans. Software Eng. 48(12): 4818-4837 (2022) - [c5]Antonio Mastropaolo, Luca Pascarella, Gabriele Bavota:
Using Deep Learning to Generate Complete Log Statements. ICSE 2022: 2279-2290 - [c4]Rosalia Tufano, Simone Masiero, Antonio Mastropaolo, Luca Pascarella, Denys Poshyvanyk, Gabriele Bavota:
Using Pre-Trained Models to Boost Code Review Automation. ICSE 2022: 2291-2302 - [d4]Matteo Ciniselli, Nathan Cooper, Luca Pascarella, Antonio Mastropaolo, Emad Aghajani, Denys Poshyvanyk, Massimiliano Di Penta, Gabriele Bavota:
Replication package for "An Empirical Study on the Usage of Transformer Models for Code Completion". Zenodo, 2022 - [d3]Antonio Mastropaolo, Emad Aghajani, Luca Pascarella, Gabriela Bavota:
Replication Package for: An Empirical Study on Code Comment Completion. Zenodo, 2022 - [d2]Antonio Mastropaolo, Luca Pascarella, Gabriele Bavota:
Replication Package for: Using Deep Learning to Generate Complete Log Statements. Zenodo, 2022 - [d1]Antonio Mastropaolo, Simone Scalabrino, Nathan Cooper, David Nader-Palacio, Denys Poshyvanyk, Rocco Oliveto, Gabriele Bavota:
Replication Package for: Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks. Zenodo, 2022 - [i7]Antonio Mastropaolo, Luca Pascarella, Gabriele Bavota:
Using Deep Learning to Generate Complete Log Statements. CoRR abs/2201.04837 (2022) - [i6]Rosalia Tufano, Simone Masiero, Antonio Mastropaolo, Luca Pascarella, Denys Poshyvanyk, Gabriele Bavota:
Using Pre-Trained Models to Boost Code Review Automation. CoRR abs/2201.06850 (2022) - [i5]Antonio Mastropaolo, Nathan Cooper, David Nader-Palacio, Simone Scalabrino, Denys Poshyvanyk, Rocco Oliveto, Gabriele Bavota:
Using Transfer Learning for Code-Related Tasks. CoRR abs/2206.08574 (2022) - [i4]Antonio Mastropaolo, Emad Aghajani, Luca Pascarella, Gabriele Bavota:
Automated Variable Renaming: Are We There Yet? CoRR abs/2212.05738 (2022) - 2021
- [j1]Simone Scalabrino, Antonio Mastropaolo, Gabriele Bavota, Rocco Oliveto:
An Adaptive Search Budget Allocation Approach for Search-Based Test Case Generation. ACM Trans. Softw. Eng. Methodol. 30(3): 36:1-36:26 (2021) - [c3]Antonio Mastropaolo, Simone Scalabrino, Nathan Cooper, David Nader-Palacio, Denys Poshyvanyk, Rocco Oliveto, Gabriele Bavota:
Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks. ICSE 2021: 336-347 - [c2]Antonio Mastropaolo, Emad Aghajani, Luca Pascarella, Gabriele Bavota:
An Empirical Study on Code Comment Completion. ICSME 2021: 159-170 - [i3]Antonio Mastropaolo, Simone Scalabrino, Nathan Cooper, David Nader-Palacio, Denys Poshyvanyk, Rocco Oliveto, Gabriele Bavota:
Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks. CoRR abs/2102.02017 (2021) - [i2]Antonio Mastropaolo, Emad Aghajani, Luca Pascarella, Gabriele Bavota:
An Empirical Study on Code Comment Completion. CoRR abs/2107.10544 (2021) - [i1]Matteo Ciniselli, Nathan Cooper, Luca Pascarella, Antonio Mastropaolo, Emad Aghajani, Denys Poshyvanyk, Massimiliano Di Penta, Gabriele Bavota:
An Empirical Study on the Usage of Transformer Models for Code Completion. CoRR abs/2108.01585 (2021)
2010 – 2019
- 2013
- [c1]Antonio Mastropaolo, Francesco Pallante, Daniele Paolo Radicioni:
Legal documents categorization by compression. ICAIL 2013: 92-100
Coauthor Index
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