Demo Data from SIGIR 2026 / reviewers in the wild / expert
F.-W. Scholz
dblp:58/1196
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1986
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 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.
| 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
software reliability modeling |
0.0 | 1 | 1986 | Software Reliability Modeling and Analysis · IEEE Trans. Software Eng. 1986 |
Software testing › software reliability › software reliability modeling
software reliability growth model |
0.0 | 1 | 1986 | Software Reliability Modeling and Analysis · IEEE Trans. Software Eng. 1986 |
Methods — techniques the papers use, named apart from their topics
statistical modeling · 0.0order statistics · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1986 | Software Reliability Modeling and AnalysisabstractA discrete and, as approximation to it, a continuous model for the software reliability growth process are examined. The discrete model is based on independent multinomial trials and concerns itself with the joint distribution of the first occurrence time of its underlying events (bugs). The continuous model is based on the order statistics ofNindependent nonidentically distributed exponential random variables. It is shown that the spacings between bugs are not necessarily independent, or exponentially (geometrically) distributed. However, there is a statistical rationale for viewing them so conditionally. Some identifiability problems are pointed out and resolved. In particular, it appears that the number of bugs in a program is not identifiable. F.-W. Scholz |
IEEE Trans. Software Eng. | 1 |