Demo Data from VLDB 2026 / reviewers in the wild / expert
Denise Varner
dblp:46/1152
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
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 |
Embedded and real-time systems · 87% Distributed systems · 13% | |
| Software engineering, system software, and programming languages
1 paper |
Requirements engineering and software design · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Requirements engineering and software design › model-driven engineering
model-based design |
0.0 | 1 | 2004 | A Model-Based Approach to Designing QoS Adaptive Applications · RTSS 2004 |
Embedded and real-time systems
cyber-physical system platforms |
0.0 | 1 | 2004 | A Model-Based Approach to Designing QoS Adaptive Applications · RTSS 2004 |
Embedded and real-time systems › distributed real-time systems
distributed real-time embedded systems |
0.0 | 1 | 2004 | A Model-Based Approach to Designing QoS Adaptive Applications · RTSS 2004 |
Distributed systems › self-adaptive systems
quality of service adaptation |
0.0 | 1 | 2004 | A Model-Based Approach to Designing QoS Adaptive Applications · RTSS 2004 |
Methods — techniques the papers use, named apart from their topics
domain-specific modeling · 0.1code synthesis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2004 | A Model-Based Approach to Designing QoS Adaptive ApplicationsabstractIn this paper we present a model-based approach for designing quality of service adaptive applications. We have developed a prototype distributed QoS modeling environment (DQME) that captures important elements of dynamic QoS adaptation at the model level. This modeling environment is designed independent of and can be integrated with, specific application domains to capture their QoS features and adaptation strategies. It combines the domain-specific modeling capability of the generic modeling environment with the QoS adaptation mechanisms of the quality objects middleware framework. DQME captures both the QoS and the functional concerns of distributed real-time embedded systems, and provides clear separation of these two. Integrated code-synthesis tools facilitate code generation and model refinement. We present a signal analyzer case study to demonstrate the use of the DQME modeling tool in real world applications. Jianming Ye, Joseph P. Loyall, Richard Shapiro, Richard E. Schantz, Sandeep Neema, Sherif Abdelwahed, Nagabhushan Mahadevan, Michael A. Koets, Denise Varner |
RTSS | 9 |