Current projects

ArtistDesign (EU)

The strategic objective of the ArtistDesign Network of Excellence is to strengthen European research in Embedded Systems Design, and promote the emergence of this new multi-disciplinary area. Operationally, this is achieved by integrating the teams, and building excellence. It gathers together the best European teams from the composing disciplines, and works to forge a scientific community. Integration is achieved around a Joint Programme of Activities, aiming to create critical mass from the selected European teams.

For more information please see the ArtistDesign home page.

SEBASE (EPSRC)

The SEBASE project aims to provide a new approach to the way in which software engineering is understood, by moving software engineering problems from human-based search to machine-based search.

For more information please see the SEBASE home page.

SSEI (MoD)

Our part of this project aims to provide improved design, verification and certification practices for the use of FPGAs in critical systems.

For more information please see the SSEI home page.

DCSC - Dependable Computing Systems Centre (BAE SYSTEMS)

The DCSC symbolises a long-term relationship between industry and academia with the members being BAE SYSTEMS, the University of York and the University of Newcastle. The role of the RTS Group within the DCSC has historically addressed the implementation aspects of real-time systems development. Particular areas of focus have included: scheduling and timing analysis (including WCET analysis), real-time programming languages, real-time kernels. More recently the research group has focussed on architecture assessment and trade-off analysis (including optimisation of timing and reliability properties of dependable systems), and the use of FPGAs as an alternative platform to COTS microprocessors.

For more information please see the DCSC home page.

Using Machine Learning in Embedded Real-Time Systems (EPSRC)

This project aims to provide new ways of inferring models from systems using techniques from Artificial Intelligence and more specifically Machine Learning. These models are initially to be used to solve problems in Worst-Case Execution Time Analysis.

For more information please see the project home page.

Tempo (EPRSC)

Indeed (EPRSC)

HiJaC (EPRSC)

Jeopard (EPRSC)

Mades (EU)