EDBT 2026 Demo / reviewers in the wild / expert
Florent Anseaume
dblp:167/0228
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—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 |
Program verification · 77% Requirements engineering and software design · 23% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Embedded and real-time systems · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program verification
formal proof |
0.2 | 1 | 2015 | Improving Predictability, Efficiency and Trust of Model-Based Proof Activity · ICSE (2) 2015 |
Embedded and real-time systems
model-based design |
0.2 | 1 | 2015 | Improving Predictability, Efficiency and Trust of Model-Based Proof Activity · ICSE (2) 2015 |
Requirements engineering and software design
model-driven engineering |
0.1 | 1 | 2015 | Improving Predictability, Efficiency and Trust of Model-Based Proof Activity · ICSE (2) 2015 |
Methods — techniques the papers use, named apart from their topics
model-based design · 0.4formal methods · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Improving Predictability, Efficiency and Trust of Model-Based Proof ActivityabstractWe report on our industrial experience in using formal methods for the analysis of safety-critical systems developed in a model-based design framework. We first highlight the formal proof workflow devised for the verification and validation of embedded systems developed in Matlab/Simulink. In particular, we show that there is a need to: determine the compatibility of the model to be analysed with the proof engine, establish whether the model facilitates proof convergence or when optimisation is required, and avoid over-specification when specifying the hypotheses constraining the inputs of the model during analysis. We also stress on the importance of having a certain harness over the proof activity and present a set of tools we developed to achieve this purpose. Finally, we give a list of best practices, methods and any necessary tools aiming at guaranteeing the validity of the verification results obtained. Jean-Frédéric Étienne, Manuel Maarek, Florent Anseaume, Véronique Delebarre |
ICSE (2) | 3 |