Demo Data from EDBT 2026 / reviewers in the wild / expert
Kay K. Mazuy
dblp:180/6369
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1964
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 |
Performance modeling and evaluation · 50% Integrated circuit design · 50% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Performance modeling and evaluation › statistical analysis › statistical performance analysis › statistical performance modeling
empirical performance modeling |
0.0 | 1 | 1964 | Mathematical Models for Predicting Pulse Characteristics in Digital Logic Systems · IEEE Trans. Electron. Comput. 1964 |
Methods — techniques the papers use, named apart from their topics
statistical analysis · 0.0regression fitting · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1964 | Mathematical Models for Predicting Pulse Characteristics in Digital Logic SystemsabstractThe multiple use of a relatively few types of basic building blocks in digital computers requires that the system designer know the actual performance characteristics of these units in order to produce optimum designs. Worst-case analysis procedures do not yield realistic performance data. The performance-prediction technique discussed in this paper is based on the development of empirical mathematical models which relate the performance variables of interest to the pertinent system parameters. Prediction equations are fitted for the logic elements in a parity-check network for rise, fall, delay, and storage times as a function of the fan-in and fan-out of the logic element and the fan-in and fan-out of the stages which drive it. A statistical analysis of the prediction equations is made to determine the validity of the models. The goodness of fit of these models is presented in graphical form. J. B. Tommerdahl, A. C. Nelson, Kay K. Mazuy |
IEEE Trans. Electron. Comput. | 3 |