Demo Data from EDBT 2026 / reviewers in the wild / expert
Berit Grußien
dblp:94/9507
· DBLP profile ↗
5ranked-venue papers
4as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 5 · 4 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.
| Theoretical computer science
1 paper |
Computational complexity · 54% Graph algorithms and graph theory · 46% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational complexity
descriptive complexity |
0.3 | 1 | 2017 | Capturing polynomial time using Modular Decomposition · LICS 2017 |
Computational complexity › descriptive complexity
fixed-point logic with counting |
0.3 | 1 | 2017 | Capturing polynomial time using Modular Decomposition · LICS 2017 |
Graph algorithms and graph theory
graph decomposition |
0.3 | 1 | 2017 | Capturing polynomial time using Modular Decomposition · LICS 2017 |
Graph algorithms and graph theory › graph decomposition
modular decomposition |
0.3 | 1 | 2017 | Capturing polynomial time using Modular Decomposition · LICS 2017 |
Computational complexity › space complexity
logarithmic space |
0.1 | 1 | 2017 | Capturing polynomial time using Modular Decomposition · LICS 2017 |
Methods — techniques the papers use, named apart from their topics
modular decomposition · 0.3canonization · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Capturing Polynomial Time using Modular Decomposition
Berit Grußien |
Log. Methods Comput. Sci. | 1 |
| 2019 | Capturing Logarithmic Space and Polynomial Time on Chordal Claw-Free GraphsabstractWe show that the class of chordal claw-free graphs admits LREC$_=$-definable canonization. LREC$_=$ is a logic that extends first-order logic with counting by an operator that allows it to formalize a limited form of recursion. This operator can be evaluated in logarithmic space. It follows that there exists a logarithmic-space canonization algorithm, and therefore a logarithmic-space isomorphism test, for the class of chordal claw-free graphs. As a further consequence, LREC$_=$ captures logarithmic space on this graph class. Since LREC$_=$ is contained in fixed-point logic with counting, we also obtain that fixed-point logic with counting captures polynomial time on the class of chordal claw-free graphs. Comment: 34 pages, 13 figures Berit Grußien |
Log. Methods Comput. Sci. | 1 |
| 2017 | Capturing Logarithmic Space and Polynomial Time on Chordal Claw-Free GraphsabstractWe show that the class of chordal claw-free graphs admits LREC=-definable canonization. LREC= is a logic that extends first-order logic with counting by an operator that allows it to formalize a limited form of recursion. This operator can be evaluated in logarithmic space. It follows that there exists a logarithmic-space canonization algorithm for the class of chordal claw-free graphs, and that LREC= captures logarithmic space on this graph class. Since LREC= is contained in fixed-point logic with counting, we also obtain that fixed-point logic with counting captures polynomial time on the class of chordal claw-free graphs. Berit Grußien |
CSL | 1 |
| 2017 | Capturing polynomial time using Modular DecompositionabstractThe question of whether there is a logic that captures polynomial time is one of the main open problems in descriptive complexity theory and database theory. In 2010 Grohe showed that fixed point logic with counting captures polynomial time on all classes of graphs with excluded minors. We now consider classes of graphs with excluded induced subgraphs. For such graph classes, an effective graph decomposition, called modular decomposition, was introduced by Gallai in 1976. The graphs that are non-decomposable with respect to modular decomposition are called prime. We present a tool, the Modular Decomposition Theorem, that reduces (definable) canonization of a graph class C to (definable) canonization of the class of prime graphs of C that are colored with binary relations on a linearly ordered set. By an application of the Modular Decomposition Theorem, we show that fixed point logic with counting also captures polynomial time on the class of permutation graphs. As a side effect of the Modular Decomposition Theorem, we further obtain that the modular decomposition tree is computable in logarithmic space. It follows that cograph recognition and cograph canonization is computable in logarithmic space. Berit Grußien |
LICS | 1 |
| 2013 | Arc consistency and friendsabstractA natural and established way to restrict the constraint satisfaction problem is to fix the relations that can be used to pose constraints; such a family of relations is called a constraint language.In this article, we study arc consistency, a heavily investigated inference method, and three extensions thereof from the perspective of constraint languages.We conduct a comparison of the studied methods on the basis of which constraint languages they solve, and we present new polynomial-time tractability results for singleton arc consistency, the most powerful method studied. Hubie Chen, Víctor Dalmau, Berit Grußien |
J. Log. Comput. | 3 |