Demo Data from EDBT 2026 / reviewers in the wild / expert
Vincent Hui
dblp:282/6358
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0001-7634-6751ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 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 |
Program verification · 50% Software maintenance and evolution · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software maintenance and evolution
change impact analysis |
0.4 | 1 | 2020 | Scaling Client-Specific Equivalence Checking via Impact Boundary Search · ASE 2020 |
Program verification
equivalence checking |
0.4 | 1 | 2020 | Scaling Client-Specific Equivalence Checking via Impact Boundary Search · ASE 2020 |
Methods — techniques the papers use, named apart from their topics
control-flow search · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Verification by Gambling on Program Slices
Murad Akhundov, Federico Mora 0002, Nick Feng, Vincent Hui, Marsha Chechik |
ATVA | 4 |
| 2020 | Scaling Client-Specific Equivalence Checking via Impact Boundary SearchabstractClient-specific equivalence checking (CSEC) is a technique proposed previously to perform impact analysis of changes to downstream components (libraries) from the perspective of an unchanged system (client). Existing analysis techniques, whether general (regression verification, equivalence checking) or special-purpose, when applied to CSEC, either require users to provide specifications, or do not scale. We propose a novel solution to the CSEC problem, called 2clever, that is based on searching the control-flow of a program for impact boundaries. We evaluate a prototype implementation of 2clever on a comprehensive set of benchmarks and conclude that our prototype performs well compared to the state-of-the-art. Nick Feng, Federico Mora 0002, Vincent Hui, Marsha Chechik |
ASE | 3 |