1 citations · 1 across the 4 of their papers we have counts for
4 papers
Enhancing Code Generation for Low-Resource Languages: No Silver Bullet
Alessandro Giagnorio, Alberto Martin-Lopez, Gabriele Bavota
The advent of Large Language Models (LLMs) has significantly advanced the field of automated code generation. LLMs rely on large and diverse datasets to learn syntax, semantics, an…
Deep Learning-based Code Completion: On the Impact on Performance of Contextual Information
Matteo Ciniselli, Luca Pascarella, Gabriele Bavota
Code completion aims at speeding up code writing by recommending to developers the next tokens they are likely to type. Deep Learning (DL) models pushed the boundaries of code comp…
On the Generalizability of Transformer Models to Code Completions of Different Lengths
Nathan Cooper, Rosalia Tufano, Gabriele Bavota +1
The programming landscape is nowadays being reshaped by the advent of Large Language Models (LLMs) able to automate code-related tasks related to code implementation (e.g., code co…
SEART Data Hub: Streamlining Large-Scale Source Code Mining and Pre-Processing
Ozren Dabić, Rosalia Tufano, Gabriele Bavota
Large-scale code datasets have acquired an increasingly central role in software engineering (SE) research. This is the result of (i) the success of the mining software repositorie…