98 citations · 122 across the 16 of their papers we have counts for
6 papers · 1 filter
Log Statements Generation via Deep Learning: Widening the Support Provided to Developers
Antonio Mastropaolo, Valentina Ferrari, Luca Pascarella +1
Logging assists in monitoring events that transpire during the execution of software. Previous research has highlighted the challenges confronted by developers when it comes to log…
On the Empirical Evidence of Microservice Logical Coupling. A Registered Report
Dario Amoroso d Aragona, Luca Pascarella, Andrea Janes +3
[Context] Coupling is a widely discussed metric by software engineers while developing complex software systems, often referred to as a crucial factor and symptom of a poor or good…
Breaks and Code Quality: Investigating the Impact of Forgetting on Software Development. A Registered Report
Dario Amoroso d'Aragona, Luca Pascarella, Andrea Janes +3
Developers interrupting their participation in a project might slowly forget critical information about the code, such as its intended purpose, structure, the impact of external de…
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…
Automating Code-Related Tasks Through Transformers: The Impact of Pre-training
Rosalia Tufano, Luca Pascarella, Gabriele Bavota
Transformers have gained popularity in the software engineering (SE) literature. These deep learning models are usually pre-trained through a self-supervised objective, meant to pr…
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…