Project Details
MegaModelling at Runtime - scalable model-based framework for continuous development and runtime validation of complex systems.
Project Period: 1. 4. 2017 - 31. 3. 2020
Project Type: grant
Code: 737494
Agency: ECSEL Joint Undertaking
Program: Horizon 2020
Systems engineering, Simulation and design tools, Software design validation and maintenance, Embedded systems, Model-based System Engineering, Model-based Testing, Models@Runtime, Megamodelling, Runtime verification, Runtime validation, Online testing, Traceability, Continuous development.
European industry faces stiff competition on the global arena. Electronic Components and Systems become more and more complex, thus calling for modern engineering practices to be applied in order to better tackle both productivity and quality. Model-based technologies promise significant productivity gains, which have already been proven in several studies and applications. However, these technologies still need more enhancements to scale up for real-life industrial projects and to provide more benefits in different contexts. The ultimate objective of improving productivity, while reducing costs and ensuring quality in development, integration and maintenance, can be achieved by using techniques integrating seamlessly design time and runtime aspects. Industrial scale system models, which are usually multi-disciplinary, multi-teams and serving to several product lines have to be be exploited at runtime, e.g. by advanced tracing and monitoring, thus boosting the overall quality of the final system and providing lessons-learnt for future product generations. MegaM@Rt brings model-based engineering to the next level in order to help European industry reducing development and maintenance costs while reinforcing both productivity and quality. To achieve that, MegaM@Rt will create a framework incorporating methods and tools for continuous development and runtime validation to significantly improve productivity, quality and predictability of large and complex industrial systems. MegaM@Rt addresses the scalability challenges with advanced megamodelling and traceability approaches, while runtime aspects will be tackled via so-called "models@runtime", online testing and execution traces analysis. MegaM@Rt brings together a strong international consortium involving experts from France, Spain, Italy and Finland. The partners cover the whole value chain from research organizations to tool providers, including 9 end-users with large industrial case studies for results validation.
Zemčík Pavel, prof. Dr. Ing. (UPGM FIT VUT) , team leader
2019
- SADOVYKH Andrey, TRUSCAN Dragos, PIERINI Pierluigi, WIDFORSS Gunnar, ASHRAF Adnan, BRUNELIERE Hugo, SMRŽ Pavel, BAGNATO Alessandra, AFZAL Wasif and HORTELANO Alexandra E. On the Use of Hackathons to Enhance Collaboration in Large Collaborative Projects. In: Proceedings of the 2019 Design, Automation and Test in Europe Conference and Exhibition, DATE 2019. Design Automation and Test in Europe Conference and Exhibition. New York: Institute of Electrical and Electronics Engineers, 2019, pp. 498-503. ISBN 978-3-9819263-2-3. Detail
2018
- AFZAL Wasif, BRUNELIERE Hugo, DI Ruscio Davide, SADOVYKH Andrey, MAZZINI Sylvia, CARIOU Eric, TRUSCAN Dragos, CABOT Jordi, FIELD Daniel, POMANTE Luigi and SMRŽ Pavel. The MegaM@Rt2 ECSEL Project: MegaModelling at Runtime - Scalable Model-Based Framework for Continuous Development and Runtime Validation of Complex Systems. In: Proceedings of the Euromicro Conference on Digital System Design (DSD). Vienna: IEEE Computer Society, 2018, pp. 494-501. ISBN 978-1-5386-2146-2. Detail
- AFZAL Wasif, BRUNELIERE Hugo, DI Ruscio Davide, SADOVYKH Andrey, MAZZINI Sylvia, CARIOU Eric, TRUSCAN Dragos, CABOT Jordi, GÓMEZ Abel, GORRONOGOITIA Jesús, POMANTE Luigi and SMRŽ Pavel. The MegaM@Rt2 ECSEL Project: MegaModelling at Runtime - Scalable Model-Based Framework for Continuous Development and Runtime Validation of Complex Systems. Microprocessors and Microsystems, vol. 61, no. 9, 2018, pp. 86-95. ISSN 0141-9331. Detail
2017
- FAJČÍK Martin, SMRŽ Pavel and ZACHARIÁŠOVÁ Marcela. Automation of Processor Verification Using Recurrent Neural Networks. In: 18th International Workshop on Microprocessor and SOC Test, Security and Verification (MTV). Austin, Texas: Institute of Electrical and Electronics Engineers, 2017, pp. 15-20. ISBN 978-1-5386-3351-9. Detail