Demo Data from EDBT 2026 / reviewers in the wild / expert
David Stefan
dblp:145/4084
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—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 |
Requirements engineering and software design · 50% Empirical software engineering · 50% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Requirements engineering and software design › software architecture › architectural design
architectural decision making |
0.2 | 1 | 2014 | Uncertainty, risk, and information value in software requirements and architecture · ICSE 2014 |
Empirical software engineering
software effort estimation |
0.2 | 1 | 2014 | Uncertainty, risk, and information value in software requirements and architecture · ICSE 2014 |
Mathematical optimization
multi-objective optimization |
0.1 | 1 | 2014 | Uncertainty, risk, and information value in software requirements and architecture · ICSE 2014 |
Methods — techniques the papers use, named apart from their topics
multi-objective optimization · 0.4monte carlo simulation · 0.4decision analysis · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Uncertainty, risk, and information value in software requirements and architectureabstractUncertainty complicates early requirements and architecture decisions and may expose a software project to significant risk. Yet software architects lack support for evaluating uncertainty, its impact on risk, and the value of reducing uncertainty before making critical decisions. We propose to apply decision analysis and multi-objective optimisation techniques to provide such support. We present a systematic method allowing software architects to describe uncertainty about the impact of alternatives on stakeholders' goals; to calculate the consequences of uncertainty through Monte-Carlo simulation; to shortlist candidate architectures based on expected costs, benefits and risks; and to assess the value of obtaining additional information before deciding. We demonstrate our method on the design of a system for coordinating emergency response teams. Our approach highlights the need for requirements engineering and software cost estimation methods to disclose uncertainty instead of hiding it. Emmanuel Letier, David Stefan, Earl T. Barr |
ICSE | 2 |