VLDB 2026 Research / reviewers in the wild / expert

Kenneth J. Yang

dblp:390/7750 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0005-0809-2792ORCID · 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 · 87% Software testing · 13%

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

TopicWeightPapersLastEvidence papers
Software maintenance and evolution › software merging
merge conflict resolution		 0.812024
Evaluation of Version Control Merge Tools · ASE 2024
Software maintenance and evolution › software configuration management
version control		 0.812024
Evaluation of Version Control Merge Tools · ASE 2024
Software testing
regression testing		 0.212024
Evaluation of Version Control Merge Tools · ASE 2024

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

empirical evaluation · 0.8
YearPublicationVenuePosition
2024 Evaluation of Version Control Merge Tools
abstract
A version control system, such as Git, requires a way to integrate changes from different developers or branches. Given a merge scenario, a merge tool either outputs a clean integration of the changes, or it outputs a conflict for manual resolution. A clean integration is correct if it preserves intended program behavior, and is incorrect otherwise (e.g., if it causes a test failure). Manual resolution consumes valuable developer time, and correcting a defect introduced by an incorrect merge is even more costly.
Benedikt Schesch, Ryan Featherman, Kenneth J. Yang, Ben R. Roberts, Michael D. Ernst
 ASE3