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Ph.D de

Ph.D
Group : Verification of Algorithms, Languages and Systems

Inférence d'invariants pour le model checking de systèmes paramétrés

Starts on 03/10/2011
Advisor : CONCHON, Sylvain
[ZAIDI Fatiha]

Funding :
Affiliation : Université Paris-Saclay
Laboratory : LRI PROVAL

Defended on 29/09/2014, committee :
Directeur de thèse :
- M. Sylvain Conchon, Professeur, Université Paris-Sud

Co-encadrante :
- Mme Fatiha Zaïdi, Maître de conférences, Université Paris-Sud

Rapporteurs :
- M. Ahmed Bouajjani, Professeur, Université Paris Diderot et IUF
- M. Silvio Ranise, Chercheur, Fondazione Bruno Kessler

Examinateurs :
- M. Rémi Delmas, Ingénieur de recherche, ONERA
- M. Alan Schmitt, Chargé de recherche, INRIA Rennes Bretagne Atlantique
- M. Philippe Dague, Professeur, Université Paris-Sud

Research activities :
   - Automated Proof, SMT and Applications

Abstract :
This thesis tackles the problem of automatically verifying complex
parameterized systems. This approach is important because it can guarantee that
some properties hold without knowing a priori the number of components in the
system. We focus in particular on the safety of such systems and we handle the
parameterized aspect with symbolic methods. This work is set in the theoretical
framework of the model checking modulo theories and resulted in a new model
checker: Cubicle.

One of the main contribution of this thesis is a novel technique for
automatically inferring invariants. The process of invariant generation is
integrated with the model checking algorithm and allows the verification in
practice of systems which are out of reach for traditional symbolic
approaches. One successful application of this algorithm is the safety analysis
of industrial size parameterized cache coherence protocols.

Finally, to address the problem of trusting the answer given by the model
checker, we present two techniques for certifying our tool Cubicle based on the
framework Why3. The first consists in producing certificates whose validity can
be assessed independently while the second is an approach by deductive
verification of the heart of Cubicle.

Ph.D. dissertations & Faculty habilitations
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CAUSAL UNCERTAINTY QUANTIFICATION UNDER PARTIAL KNOWLEDGE AND LOW DATA REGIMES


MICRO VISUALIZATIONS: DESIGN AND ANALYSIS OF VISUALIZATIONS FOR SMALL DISPLAY SPACES
The topic of this habilitation is the study of very small data visualizations, micro visualizations, in display contexts that can only dedicate minimal rendering space for data representations. For several years, together with my collaborators, I have been studying human perception, interaction, and analysis with micro visualizations in multiple contexts. In this document I bring together three of my research streams related to micro visualizations: data glyphs, where my joint research focused on studying the perception of small-multiple micro visualizations, word-scale visualizations, where my joint research focused on small visualizations embedded in text-documents, and small mobile data visualizations for smartwatches or fitness trackers. I consider these types of small visualizations together under the umbrella term ``micro visualizations.'' Micro visualizations are useful in multiple visualization contexts and I have been working towards a better understanding of the complexities involved in designing and using micro visualizations. Here, I define the term micro visualization, summarize my own and other past research and design guidelines and outline several design spaces for different types of micro visualizations based on some of the work I was involved in since my PhD.