EDBT 2026 Demo / reviewers in the wild / expert
Laure Millet
dblp:149/2504
· DBLP profile ↗
5ranked-venue papers
3as first author
2since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 3 · 2 first-author · 2 since 2021Systems, architecture and hardware · 1Software engineering, systems software and programming languages · 1 · 1 first-author
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Balancing the Risks and Benefits of Using Large Language Models to Support Assurance Case Development
Simon Diemert, Erin Cyffka, Naweed Anwari, Olivia Foster, Torin Viger, Laure Millet, Jeffrey J. Joyce |
SAFECOMP | 6 |
| 2023 | Assurance Case Arguments in the Large: The CERN LHC Machine Protection System
Laure Millet, Simon Diemert, Chris Rees, Torin Viger, Marsha Chechik, Claudio Menghi, Jeffrey J. Joyce |
SAFECOMP | 1 |
| 2018 | Morse: Reducing the Feature Interaction Explosion Problem using Subject Matter Knowledge as Abstract RequirementsabstractThe feature interaction problem appears in many different kinds of complex systems, especially systems whose elements are created or maintained by separate entities - for example, a modern automobile that incorporates electronic systems produced by different suppliers. Cross-cutting concerns, such as safety and security, require a comprehensive analysis of the possible interactions. However, there is a combinatorial explosion in the number of feature combinations to be considered. Our work approaches the feature interaction problem from a novel point of view: we seek to use the abstract subject matter knowledge of domain experts to deduce why some features will NOT interact, rather than trying to discover or resolve the interactions. In this paper, we present a method that can automatically reduce the required number of combinations and situations that have to be evaluated or resolved for feature interactions. Our tool, called Morse, rules out feature combinations that cannot have interactions based on traceable deductions from relatively simple abstract requirements that capture relevant subject matter knowledge. Our method is useful as a means of focusing attention on particular situations where more detailed functional requirements may be needed to avoid unacceptable risk arising from unintended interactions between features. relatively simple abstract requirements that capture relevant subject matter knowledge. Our method is useful as a means of focusing attention on particular situations where more detailed functional requirements may be needed to avoid unacceptable risk arising from unintended interactions between features. Laure Millet, Nancy A. Day, Jeffrey J. Joyce |
RE | 1 |
| 2016 | Formal verification of mobile robot protocols
Béatrice Bérard, Pascal Lafourcade 0001, Laure Millet, Maria Potop-Butucaru, Yann Thierry-Mieg, Sébastien Tixeuil |
Distributed Comput. | 3 |
| 2014 | On the Synthesis of Mobile Robots Algorithms: The Case of Ring Gathering
Laure Millet, Maria Potop-Butucaru, Nathalie Sznajder, Sébastien Tixeuil |
SSS | 1 |