EDBT 2026 Demo / reviewers in the wild / expert
Huazheng Zeng
dblp:386/5309
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0002-4495-6728ORCID · reported
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 · 100% |
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
forking |
0.8 | 1 | 2024 | Your "Notice" Is Missing: Detecting and Fixing Violations of Modification Terms in Open Source Licenses during Forking · ISSTA 2024 |
Software maintenance and evolution › software ecosystems
license compliance |
0.8 | 1 | 2024 | Your "Notice" Is Missing: Detecting and Fixing Violations of Modification Terms in Open Source Licenses during Forking · ISSTA 2024 |
Software maintenance and evolution
software ecosystems |
0.8 | 1 | 2024 | Your "Notice" Is Missing: Detecting and Fixing Violations of Modification Terms in Open Source Licenses during Forking · ISSTA 2024 |
Methods — techniques the papers use, named apart from their topics
empirical study · 0.8automated detection and repair · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Your "Notice" Is Missing: Detecting and Fixing Violations of Modification Terms in Open Source Licenses during ForkingabstractOpen source software brings benefit to the software community but also introduces legal risks caused by license violations, which result in serious consequences such as lawsuits and financial losses. To mitigate legal risks, some approaches have been proposed to identify licenses, detect license incompatibilities and inconsistencies, and recommend licenses. As far as we know, however, there is no prior work to understand modification terms in open source licenses or to detect and fix violations of modification terms. To bridge this gap, we first empirically characterize modification terms in 48 open source licenses. These licenses all require certain forms of “notice” to describe the modifications made to the original work. Inspired by our study, we then design LiVo to automatically detect and fix violations of modification terms in open source licenses during forking. Our evaluation has shown the effectiveness and efficiency of LiVo. 18 pull requests for fixing modification term violations have received positive responses. 8 have been merged. Kaifeng Huang 0001, Yingfeng Xia, Bihuan Chen 0001, Siyang He, Huazheng Zeng, Zhuotong Zhou, Xin Peng 0001 |
ISSTA | 5 |