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Vincent Hui

dblp:282/6358 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Software maintenance and evolution
change impact analysis
0.412020
Scaling Client-Specific Equivalence Checking via Impact Boundary Search · ASE 2020
Program verification
equivalence checking
0.412020
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
YearPublicationVenuePosition
2021 Verification by Gambling on Program Slices
Murad Akhundov, Federico Mora 0002, Nick Feng, Vincent Hui, Marsha Chechik
ATVA4
2020 Scaling Client-Specific Equivalence Checking via Impact Boundary Search
abstract
Client-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
ASE3