7 citations · 11 across the 11 of their papers we have counts for
11 papers
Optimizing Datasets for Code Summarization: Is Code-Comment Coherence Enough?
Antonio Vitale, Antonio Mastropaolo, Rocco Oliveto +2
Automated code summarization is a long-standing goal for code comprehension. This task automatically generates documentation using a given method. Deep Learning (DL)-based approach…
Resource-Efficient & Effective Code Summarization
Saima Afrin, Joseph Call, Khai-Nguyen Nguyen +2
Code Language Models (CLMs) have demonstrated high effectiveness in automating software engineering tasks such as bug fixing, code generation, and code documentation. This progress…
Toward Neurosymbolic Program Comprehension
Alejandro Velasco, Aya Garryyeva, David N. Palacio +2
Recent advancements in Large Language Models (LLMs) have paved the way for Large Code Models (LCMs), enabling automation in complex software engineering tasks, such as code generat…
The Rise and Fall(?) of Software Engineering
Antonio Mastropaolo, Camilo Escobar-Velásquez, Mario Linares-Vásquez
Over the last ten years, the realm of Artificial Intelligence (AI) has experienced an explosion of revolutionary breakthroughs, transforming what seemed like a far-off dream into a…
How the Training Procedure Impacts the Performance of Deep Learning-based Vulnerability Patching
Antonio Mastropaolo, Vittoria Nardone, Gabriele Bavota +1
Generative deep learning (DL) models have been successfully adopted for vulnerability patching. However, such models require the availability of a large dataset of patches to learn…
Unveiling ChatGPT's Usage in Open Source Projects: A Mining-based Study
Rosalia Tufano, Antonio Mastropaolo, Federica Pepe +3
Large Language Models (LLMs) have gained significant attention in the software engineering community. Nowadays developers have the possibility to exploit these models through indus…