Demo Data from EDBT 2026 / reviewers in the wild / expert
Beatrix Braune
dblp:46/1614
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2000
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
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.
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics › software visualization
algorithm visualization |
0.0 | 1 | 2000 | Focusing in Algorithm Explanation · IEEE Trans. Vis. Comput. Graph. 2000 |
Visualization and visual analytics
visual analytics |
0.0 | 1 | 2000 | Focusing in Algorithm Explanation · IEEE Trans. Vis. Comput. Graph. 2000 |
Visualization and visual analytics
image abstraction |
0.0 | 1 | 2000 | Focusing in Algorithm Explanation · IEEE Trans. Vis. Comput. Graph. 2000 |
Visualization and visual analytics
visual encoding |
0.0 | 1 | 2000 | Focusing in Algorithm Explanation · IEEE Trans. Vis. Comput. Graph. 2000 |
Methods — techniques the papers use, named apart from their topics
shape analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | Focusing in Algorithm ExplanationabstractAlgorithm animation attempts to explain an algorithm by visualizing interesting events of the execution of the implemented algorithm on some sample input. Algorithm explanation describes the algorithm on some adequate level of abstraction, states invariants, explains how important steps of the algorithm preserve the invariants, and abstracts from the input data up to the relevant properties. It uses a small focus onto the execution state. This paper is concerned with the explanation of algorithms on linked data structures. The thesis of the paper is that shape analysis of such algorithms produces abstract representations of such data structures, which focus on the "active" parts, i.e., the parts of the data structures, which the algorithm can access during it's next steps. The paper presents a concept of visually executing an algorithm on these abstract representations of data. Beatrix Braune, Reinhard Wilhelm |
IEEE Trans. Vis. Comput. Graph. | 1 |