Demo Data from VLDB 2026 / reviewers in the wild / expert
Sören Viegener
dblp:332/5522
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
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 |
Requirements engineering and software design · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Requirements engineering and software design
software product lines |
0.6 | 1 | 2022 | Classifying edits to variability in source code · ESEC/SIGSOFT FSE 2022 |
Requirements engineering and software design › software product lines
variability management |
0.6 | 1 | 2022 | Classifying edits to variability in source code · ESEC/SIGSOFT FSE 2022 |
Methods — techniques the papers use, named apart from their topics
edit classification catalog · 0.6commit history analysis · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Classifying edits to variability in source codeabstractFor highly configurable software systems, such as the Linux kernel, maintaining and evolving variability information along changes to source code poses a major challenge. While source code itself may be edited, also feature-to-code mappings may be introduced, removed, or changed. In practice, such edits are often conducted ad-hoc and without proper documentation. To support the maintenance and evolution of variability, it is desirable to understand the impact of each edit on the variability. We propose the first complete and unambiguous classification of edits to variability in source code by means of a catalog of edit classes. This catalog is based on a scheme that can be used to build classifications that are complete and unambiguous by construction. To this end, we introduce a complete and sound model for edits to variability. In about 21.5ms per commit, we validate the correctness and suitability of our classification by classifying each edit in 1.7 million commits in the change histories of 44 open-source software systems automatically. We are able to classify all edits with syntactically correct feature-to-code mappings and find that all our edit classes occur in practice. Paul Maximilian Bittner, Christof Tinnes, Alexander Schultheiß, Sören Viegener, Timo Kehrer, Thomas Thüm |
ESEC/SIGSOFT FSE | 4 |