Matteo Ciniselli

According to our database, Matteo Ciniselli authored at least 12 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2024

Code Review Automation: Strengths and Weaknesses of the State of the Art.

Rosalia Tufano, Ozren Dabic, Antonio Mastropaolo, Matteo Ciniselli, Gabriele Bavota

IEEE Trans. Software Eng., February, 2024

From Today's Code to Tomorrow's Symphony: The AI Transformation of Developer's Routine by 2030.

Matteo Ciniselli, Niccolò Puccinelli, Ketai Qiu, Luca Di Grazia

CoRR, 2024

Towards Summarizing Code Snippets Using Pre-Trained Transformers.

Antonio Mastropaolo, Matteo Ciniselli, Luca Pascarella, Rosalia Tufano, Emad Aghajani, Gabriele Bavota

Proceedings of the 32nd IEEE/ACM International Conference on Program Comprehension, 2024

On the Generalizability of Deep Learning-based Code Completion Across Programming Language Versions.

Matteo Ciniselli, Alberto Martin-Lopez, Gabriele Bavota

Proceedings of the 32nd IEEE/ACM International Conference on Program Comprehension, 2024

Evaluating Code Summarization Techniques: A New Metric and an Empirical Characterization.

Antonio Mastropaolo, Matteo Ciniselli, Massimiliano Di Penta, Gabriele Bavota

Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024

2023

On the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot.

Antonio Mastropaolo, Luca Pascarella, Emanuela Guglielmi, Matteo Ciniselli, Simone Scalabrino, Rocco Oliveto, Gabriele Bavota

Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

Source Code Recommender Systems: The Practitioners' Perspective.

Matteo Ciniselli, Luca Pascarella, Emad Aghajani, Simone Scalabrino, Rocco Oliveto, Gabriele Bavota

Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

2022

Replication package for "An Empirical Study on the Usage of BERT Models for Code Completion".

Matteo Ciniselli, Nathan Cooper, Luca Pascarella, Denys Poshyvanyk, Massimiliano Di Penta, Gabriele Bavota

Dataset, January, 2022

Replication package for "An Empirical Study on the Usage of Transformer Models for Code Completion".

Matteo Ciniselli, Nathan Cooper, Luca Pascarella, Antonio Mastropaolo, Emad Aghajani, Denys Poshyvanyk, Massimiliano Di Penta, Gabriele Bavota

Dataset, January, 2022

An Empirical Study on the Usage of Transformer Models for Code Completion.

Matteo Ciniselli, Nathan Cooper, Luca Pascarella, Antonio Mastropaolo, Emad Aghajani, Denys Poshyvanyk, Massimiliano Di Penta, Gabriele Bavota

IEEE Trans. Software Eng., 2022

To What Extent do Deep Learning-based Code Recommenders Generate Predictions by Cloning Code from the Training Set?

Matteo Ciniselli, Luca Pascarella, Gabriele Bavota

Proceedings of the 19th IEEE/ACM International Conference on Mining Software Repositories, 2022

2021

An Empirical Study on the Usage of BERT Models for Code Completion.

Matteo Ciniselli, Nathan Cooper, Luca Pascarella, Denys Poshyvanyk, Massimiliano Di Penta, Gabriele Bavota

Proceedings of the 18th IEEE/ACM International Conference on Mining Software Repositories, 2021