most citedOn the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot

7 citations · 12 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SE2023

Automatically Generating Dockerfiles via Deep Learning: Challenges and Promises

Giovanni Rosa, Antonio Mastropaolo, Simone Scalabrino +2

Containerization allows developers to define the execution environment in which their software needs to be installed. Docker is the leading platform in this field, and developers t…

cs.SE20233 cited

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…

cs.SE20232 cited

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…

cs.SE20237 cited

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…

cs.SE2022

Don't Reinvent the Wheel: Towards Automatic Replacement of Custom Implementations with APIs

Rosalia Tufano, Emad Aghajani, Gabriele Bavota

Reusing code is a common practice in software development: It helps developers speedup the implementation task while also reducing the chances of introducing bugs, given the assump…