Demo Data from SIGIR 2026 / reviewers in the wild / expert
Yutaka Nakagawa
dblp:77/1616
· DBLP profile ↗
1ranked-venue papers
1as 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 · 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 · 56% Empirical software engineering · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering
software metrics |
0.0 | 1 | 1989 | An Error Complexity Model for Software Reliability Measurement · ICSE 1989 |
Software testing
software reliability |
0.0 | 1 | 1989 | An Error Complexity Model for Software Reliability Measurement · ICSE 1989 |
Software testing › software reliability
reliability assessment |
0.0 | 1 | 1989 | An Error Complexity Model for Software Reliability Measurement · ICSE 1989 |
Methods — techniques the papers use, named apart from their topics
statistical evaluation · 0.0error complexity modeling · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1989 | An Error Complexity Model for Software Reliability MeasurementabstractMany simple software errors are found in earlier software test phases.The ratio of complex errors to simple errors gradually increases with continual testing.This paper describes a software reliability model called the Error Complexity Model.In this model, errors are classified by error complexity which is a measure of error detectability.The number of remaining software errors is estimated from the ratio of complex to simple errors and the number of discovered errors.New criteria for error complexity classification are proposed.The model is evaluated and compared with existing models using actual error data. Yutaka Nakagawa, Shuetsu Hanata |
ICSE | 1 |