2 citations · 5 across the 9 of their papers we have counts for
9 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…
Do LLMs Provide Links to Code Similar to what they Generate? A Study with Gemini and Bing CoPilot
Daniele Bifolco, Pietro Cassieri, Giuseppe Scanniello +2
Large Language Models (LLMs) are currently used for various software development tasks, including generating code snippets to solve specific problems. Unlike reuse from the Web, LL…
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…
Toward Automatically Completing GitHub Workflows
Antonio Mastropaolo, Fiorella Zampetti, Gabriele Bavota +1
Continuous integration and delivery (CI/CD) are nowadays at the core of software development. Their benefits come at the cost of setting up and maintaining the CI/CD pipeline, whic…
Towards Automatically Addressing Self-Admitted Technical Debt: How Far Are We?
Antonio Mastropaolo, Massimiliano Di Penta, Gabriele Bavota
Upon evolving their software, organizations and individual developers have to spend a substantial effort to pay back technical debt, i.e., the fact that software is released in a s…