Taco

Abstract

Timing analysis is an important part of the development of critical real-time systems. It stems from the need to provide evidence on the behaviour of the system, compliance to requirements and timing bounds. The formal testing process is complicated, and includes tests to achieve compliance with certiication requirements. Where possible, testing should be performed on a host and then validated on the target. This is especially important for real systems where the target may not be available early in the project or target-based testing is expensive and time consuming. Meaningful host-based testing is diicult when it comes to timing analysis. Automation helps reduce the costs and move testing earlier in the application development cycle. Moving testing earlier in the development cycle not only enables the testing to scale to whole systems, it allows the risks of projects to be managed and software to be optimised before target-based testing is performed.In this paper, we extend existing work achieving reliable coverage and High WaterMark (HWM) measurement, to scale its application to the analysis of a full system software build, automate the test process, and minimise the set of tests deployed on target. Our case study demonstrates the successful application of the approach on a large code base, i.e. an existing controls system software code. The paper ends with a position statement about how this work is instrumental for both future research but also as part of industry practically analysing the timing behaviour of systems automatically and certifying mixed-criticality systems.

Justifying the Service Provided to Low Criticality Tasks in a Mixed Criticality System

“…Claim G21 concerns the input timing proiles used to generate the simulator results. As noted in the introduction to this section, the simulation is setup using a set of task timing proiles generated through task-level execution in a representative environment, as detailed further in [17]. These timing proiles provide a representative set of results for the scheduler simulation to randomly iterate over.…”