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Pierluigi Barbiero

dblp:419/5135 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software maintenance and evolution · 87% Program synthesis and code generation · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software maintenance and evolution › traceability
code provenance
0.912025
CodeGenLink: A Tool to Find the Likely Origin and License of Automatically Generated Code · ASE 2025
Software maintenance and evolution
software licensing
0.912025
CodeGenLink: A Tool to Find the Likely Origin and License of Automatically Generated Code · ASE 2025
Program synthesis and code generation
code generation with language models
0.312025
CodeGenLink: A Tool to Find the Likely Origin and License of Automatically Generated Code · ASE 2025

Methods — techniques the papers use, named apart from their topics

web search · 0.9similarity analysis · 0.9large language model · 0.9
YearPublicationVenuePosition
2025 CodeGenLink: A Tool to Find the Likely Origin and License of Automatically Generated Code
abstract
Large Language Models (LLMs) are widely used in software development tasks nowadays. Unlike reusing code taken from the Web, for LLMs' generated code, developers are concerned about its lack of trustworthiness and possible copyright or licensing violations, due to the lack of code provenance information. This paper proposes CodeGenLink, a GitHub CoPilot extension for Visual Studio Code aimed at (i) suggesting links containing code very similar to automatically generated code, and (ii) whenever possible, indicating the license of the likely origin of the code. CodeGenLink retrieves candidate links by combining LLMs with their web search features and then performs similarity analysis between the generated and retrieved code. Preliminary results show that CodeGenLink effectively filters unrelated links via similarity analysis and provides licensing information when available.Tool URL: https://github.com/danielebifolco/CodeGenLinkTool Video: https://youtu.be/M6nqjBf_pw
Daniele Bifolco, Guido Annicchiarico, Pierluigi Barbiero, Massimiliano Di Penta, Fiorella Zampetti
ASE3