Demo Data from VLDB 2026 / reviewers in the wild / expert
Stéphanie Mahévas
dblp:16/179
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2001
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 architecture, parallel and distributed computing, and storage systems
1 paper |
Performance modeling and evaluation · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Performance modeling and evaluation
markov models |
0.0 | 1 | 2001 | Bound Computation of Dependability and Performance Measures · IEEE Trans. Computers 2001 |
Performance modeling and evaluation › queueing models › queueing network model
open queueing networks |
0.0 | 1 | 2001 | Bound Computation of Dependability and Performance Measures · IEEE Trans. Computers 2001 |
Performance modeling and evaluation
queueing models |
0.0 | 1 | 2001 | Bound Computation of Dependability and Performance Measures · IEEE Trans. Computers 2001 |
Methods — techniques the papers use, named apart from their topics
markov model bounding · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | Bound Computation of Dependability and Performance MeasuresabstractWe propose a new method to obtain bounds of dependability, performance or performability measures concerning complex systems modeled by a large Markov model. It extends previously published techniques mainly designed to the analysis of dependability measures only and working under more restrictive conditions. Our approach allows us to obtain tight bounds of performance measures on certain cases and, in particular, on models having an infinite state space. We illustrate the method with some analytically intractable open queuing networks, as well as with large dependability models. Stéphanie Mahévas, Gerardo Rubino |
IEEE Trans. Computers | 1 |