Research in real-time systems has gone very far from the initial seminal papers back in the 70s. Many algorithms, design methodologies, techniques and tools have been proposed, spanning several application areas, from RTOS to distributed systems, from safety critical to soft real-time systems. However, unlike other research areas (e.g., networking) there are no widely recognized reference tools or methodologies for comparing different research works in the area.

In fact, the comparison among results achieved by different research groups becomes non-trivial or impossible due to the lack of common tools or methodologies by means of which the comparison is done. For example, different authors use different algorithms for generating random task sets, different application traces when simulating dynamic real-time systems, different simulation engines when simulating scheduling algorithms. Therefore, research in the field of real-time and embedded systems would greatly benefit from the availability of well-engineered, possibly open tools, simulation frameworks and data sets which may constitute a common metrics for evaluating simulation or experimental results in the area. Also, it would be nice to have a possibly wide set of reusable data sets or behavioural models coming from realistic industrial use-cases over which to evaluate the performance of novel algorithms. Availability of such items would increase the possibility to compare novel techniques in dealing with problems already tackled by others from the multifaceted viewpoints of effectiveness, overhead, performance, applicability, etc.

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