Section: Bilateral Contracts and Grants with Industry

Bilateral Contracts with Industry

Safran : Desir/Glose

We participate to the bilateral collaborative program Desir, put up by Safran to work with selected academic partners. We share the Glose project started in this program with two other Inria teams : HyComes, and DiverSE. The aim of the project is to improve early stages of system engineering by allowing early execution and co-simulation of heterogeneous models. The technical content of our contributions is described in section 7.13. A CIFRE PhD is funded by Renault on related topics.

IRT Saint-Exupery ATIPPIC

This cooperative project aims at building a computing digital electronic structure of micro-satellites on ordinary, "COTS" processors. The project was accepted for 30 months and will reach completion by the end of 2019. It funds two temporary research engineers working under our own supervision, while exchanging extensively with the rest of the ATIPPIC project, which is actually physically hosted by Inria. The technical content of our contributions is described in section 7.2.

Airbus

In the continuation of the ITEA3 ASSUME project, Airbus has provided funding for the extension of the Real-Time Systems Compilation method to allow parallelization onto multi-cores with classical ARM or POWER architecture. The technical content of our contributions is described in section 7.16. The technical content of our contributions is described in section 7.2.

IRT Saint-Exupery

The CAPHCA project of IRT Saint-Exupéry has provided funding for the extension of the Real-Time Systems compilation method to allow parallelization onto timing predictable multi-cores different from the Kalray MPPA 256. The targets of this work are Infineon TC27x and FlexPRET.

Renault Software Lab

We have started, at the end of 2018, a collaboration with Renault Software Labs on the definition of rules for ensuring safe maneuvers in autonomous vehicles. The rules express conditions from the environments, safety rules to preserve the integrity of the vehicles, driving legislation rules, local rules from the authorities. The rules must be updated dynamically when the vehicle evolves and are used to monitor at run-time the behavior of the ADAS. While the ADAS contains several algorithms relying on machine learning, the monitoring system must be predictive and rules must guarantee formally that the system does not cause any accident. So it can be seen as a way to build trustworthy monitoring of learning algorithms. A CIFRE PhD is funded by Renault on this topic and has started in April 2019.

Accenture Labs

We have continued discussions with Accenture Labs, started in 2018, on Smart Contract languages for permissioned blockchains. A CIFRE funding is under way.

In recent years, various platform developments focused on so-called private (or permissioned) blockchain(s) and digital ledgers. Almost all private blockchains present their own implementation of Smart Contract. Between public and private blockchains we are observing a wide variety of different languages with different capabilities and limitations. Inspired by our researches in object-oriented languages [40], we aim at designing a language which might extend an object instance upon receiving a message, an ability referred to by Cardelli as self-inflicted operation. Public and private blockchains would take advantage of this novel capability in building safe and flexible intelligent smart contracts.