7 citations · 10 across the 4 of their papers we have counts for
4 papers
On the Generalizability of Deep Learning-based Code Completion Across Programming Language Versions
Matteo Ciniselli, Alberto Martin-Lopez, Gabriele Bavota
Code completion is a key feature of Integrated Development Environments (IDEs), aimed at predicting the next tokens a developer is likely to write, helping them write code faster a…
Code Review Automation: Strengths and Weaknesses of the State of the Art
Rosalia Tufano, Ozren Dabić, Antonio Mastropaolo +2
The automation of code review has been tackled by several researchers with the goal of reducing its cost. The adoption of deep learning in software engineering pushed the automatio…
Source Code Recommender Systems: The Practitioners' Perspective
Matteo Ciniselli, Luca Pascarella, Emad Aghajani +3
The automatic generation of source code is one of the long-lasting dreams in software engineering research. Several techniques have been proposed to speed up the writing of new cod…
On the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot
Antonio Mastropaolo, Luca Pascarella, Emanuela Guglielmi +4
Software engineering research has always being concerned with the improvement of code completion approaches, which suggest the next tokens a developer will likely type while coding…