Demo Data from SIGIR 2026 / reviewers in the wild / expert
Peter Pedross
dblp:38/5369
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1998
—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 |
Empirical software engineering · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering
software size measurement |
0.0 | 1 | 1998 | Software Size Measurement and Productivity Rating in a Large-Scale Software Development Department · ICSE 1998 |
Empirical software engineering › software metrics
productivity measurement |
0.0 | 1 | 1998 | Software Size Measurement and Productivity Rating in a Large-Scale Software Development Department · ICSE 1998 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1998 | Software Size Measurement and Productivity Rating in a Large-Scale Software Development DepartmentabstractSome current object-oriented analysis methods provide use cases. Scenarios or similar concepts to describe functional requirements for software systems. The authors introduced the use case point method to measure the size of large-scale software systems based on such requirements specifications. With the measured size and the measured effort the real productivity can be calculated in terms of delivered functionality. In the status report they summarize the experiences made with size metrics and productivity rates at a major Swiss banking institute. They analyzed the quality of requirements documents and the measured use case points in order to test and calibrate the use case point method. Experiences are based on empirical data of a productivity benchmark of 23 measured projects (quantitative analysis), 64 evaluated questionnaires of project members and 11 post benchmark interviews held with selected project managers (qualitative analysis). Martin Arnold, Peter Pedross |
ICSE | 2 |