Demo Data from EDBT 2026 / reviewers in the wild / expert
Kenshin Tokunaga
dblp:44/1635
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1989
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 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.
| Software engineering, system software, and programming languages
1 paper |
Software testing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing
software reliability |
0.0 | 1 | 1989 | Structural Approach to the Estimation of the Number of Residual Software Faults Based on the Hyper-Geometric Distribution · IEEE Trans. Software Eng. 1989 |
Software testing › software reliability › software reliability modeling
software reliability growth model |
0.0 | 1 | 1989 | Structural Approach to the Estimation of the Number of Residual Software Faults Based on the Hyper-Geometric Distribution · IEEE Trans. Software Eng. 1989 |
Methods — techniques the papers use, named apart from their topics
segmentation · 0.0composite estimation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1989 | Structural Approach to the Estimation of the Number of Residual Software Faults Based on the Hyper-Geometric DistributionabstractModels based on the hyper-geometric distribution for estimating the number of residual software faults are proposed. The application of the basic model shows that its fit to real data is good. Two ways of improving the model, using a segmentation technique and composite estimation, respectively, are shown. The segmentation technique appears quite effective, particularly when the growth curve of the cumulative number of detected faults bends sharply. The applications of these models to real data are demonstrated.> Yoshihiro Tohma, Kenshin Tokunaga, Shinji Nagase, Yukihisa Murata |
IEEE Trans. Software Eng. | 2 |