Jeff Cho

dblp:278/0524 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

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

Software engineering, systems software and programming languages · 1

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 analysis · 87% Programming languages and type systems · 13%

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

TopicWeightPapersLastEvidence papers
Program analysis
static analysis
0.412020
SWAN: a static analysis framework for swift · ESEC/SIGSOFT FSE 2020
Program analysis › static analysis › static analysis tools
static analysis framework
0.412020
SWAN: a static analysis framework for swift · ESEC/SIGSOFT FSE 2020
Programming languages and type systems
language design
0.112020
SWAN: a static analysis framework for swift · ESEC/SIGSOFT FSE 2020

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

taint tracking · 0.4static analysis · 0.4
YearPublicationVenuePosition
2020 SWAN: a static analysis framework for swift
abstract
Swift is an open-source programming language and Apple's recommended choice for app development. Given the global widespread use of Apple devices, the ability to analyze Swift programs has significant impact on millions of users. Although static analysis frameworks exist for various computing platforms, there is a lack of comparable tools for Swift. While LLVM and Clang support some analyses for Swift, they are either primarily dynamic analyses or not suitable for deeper analyses of Swift programs such as taint tracking. Moreover, other existing tools for Swift only help enforce code styles and best practices.
Daniil Tiganov, Jeff Cho, Karim Ali 0001, Julian Dolby
ESEC/SIGSOFT FSE2