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Section: Partnerships and Cooperations
National Initiatives
ANR-DFG Project SMArT
Participants : Haniel Barbosa, David Déharbe, Pablo Dobal, Pascal Fontaine, Maximilian Jaroschek, Marek Košta, Stephan Merz, Thomas Sturm.
The SMArT (Satisfiability Modulo Arithmetic Theories) project is funded by ANR-DFG Programmes blancs 2013, a program of the Agence Nationale de la Recherche and the (German) Deutsche Forschungsgemeinschaft DFG. It started in April 2014. The partners are both the French and German parts of VeriDis and the Systerel company. The objective of the SMArT project is to provide advanced techniques for arithmetic reasoning beyond linear arithmetic for formal system verification, and particularly for SMT. Arithmetic reasoning is one strong direction of research at MPI, and the state-of-the-art tool Redlog (section 6.1 ) is mainly developed by Thomas Sturm. The SMT solver veriT (section 6.4 ), developed in Nancy, serves as an experimentation platform for theories, techniques and methods designed within this project.
In September 2014, Pablo Federico Dobal was hired as a PhD student in joint supervision with Saarland University, co-funded by the SMArT project and the Région Lorraine. For personal reasons, his thesis has been put on hold in September 2015.
More information on the project can be found on http://smart.gforge.inria.fr/ .
ANR Project IMPEX
Participants : Manamiary Andriamiarina, Souad Kherroubi, Dominique Méry.
The ANR Project IMPEX is an INS ANR project that started in December 2013 for 4 years. It is coordinated by Dominique Méry, the other partners are IRIT/ENSEIHT, Systerel, Supelec and Telecom Sud Paris. The work reported here also included a cooperation with Pierre Castéran from LaBRI Bordeaux.
Modeling languages provide techniques and tool support for the design, synthesis, and analysis of the models resulting from a given modeling activity, as part of a system development process. These languages quite successfully focused on the analysis of the designed system exploiting the expressed semantic power of the underlying modeling language. The semantics of this modeling languages are well understood by the system designers and the users of the modeling language, i.e. the semantics is implicit in the model. In general, modeling languages are not equipped with resources, concepts or entities handling explicitly domain engineering features and characteristics (domain knowledge) underlying the modeled systems. Indeed, the designer has to explicitly handle the knowledge resulting from an analysis of this application domain [28] , i.e. explicit semantics. Nowadays, making explicit the domain knowledge inside system design models does not obey any methodological rules validated by practice. The users of modeling languages introduce these domain knowledge features through types, constraints, profiles, etc. Our claim is that ontologies are good candidates for handling explicit domain knowledge. They define domain theories and provide resources for uniquely identifying domain knowledge concepts. Therefore, allowing models to make references to ontologies is a modular solution for models to explicitly handle domain knowledge. Overcoming the absence of explicit semantics expression in the modeling languages used to specify systems models will increase the robustness of the designed system models. Indeed, the axioms and theorems resulting from the ontologies can be used to strengthen the properties of the designed models. The objective [13] is to offer rigorous mechanisms for handling domain knowledge in design models.
Inria Technological Development Action CUIC
Participants : Jasmin Christian Blanchette, Simon Cruanes.
Most “theorems” initially given to a proof assistant are incorrect, whether because of a typo, a missing assumption, or a fundamental flaw. Novices and experts alike can enter invalid formulas and find themselves wasting hours, or even days, on an impossible proof. This project, funded by Inria and running from 2015 to 2017, supports the development of a counterexample generator for higher-order logic. This new tool, called Nunchaku, will be integrated in various proof assistants, including Isabelle, Coq, and the TLA+ Proof System. The project is coordinated by Jasmin Blanchette and also involves Inria Saclay (EPI Toccata) and Inria Rennes (EPI Celtique), among others. Simon Cruanes was hired in October 2015 and has started the development of Nunchaku, whereas Blanchette has developed a preliminary version of the Isabelle frontend. We expect a first release in early 2016.
Inria ADT PLM (2014-2016)
Participants : Martin Quinson, Matthieu Nicolas.
Joint work with Gérald Oster (project-team Coast, Inria Nancy – Grand Est).
The goal of this project is to establish an experimental platform for studying the didactics of informatics, specifically centered on introductory programming courses.
The project builds upon a pedagogical platform for supervising programming exercises developed for our own teaching, and improves this base in several ways. We want to provide more adapted feedback to the learners, and gather more data to better understand how beginners learn programming.
This year, we heavily refactored the software into a web application, to grow the user community amongst learners and thus gather more learning analytics. We also added the ability to solve PLM exercises by assembling code blocks as in Scratch. Finally, we started working on an integrated exercise editor in the hope of growing the user community amongst teachers that will be able to propose their own exercises on top of PLM.