Demo Data from VLDB 2026 / reviewers in the wild / expert
Guido Annicchiarico
dblp:419/4646
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software maintenance and evolution › traceability
code provenance |
0.9 | 1 | 2025 | CodeGenLink: A Tool to Find the Likely Origin and License of Automatically Generated Code · ASE 2025 |
Software maintenance and evolution
software licensing |
0.9 | 1 | 2025 | 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 |
0.3 | 1 | 2025 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | CodeGenLink: A Tool to Find the Likely Origin and License of Automatically Generated CodeabstractLarge 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 |
ASE | 2 |