Abstract Hybrid systems combine continuous-time and discrete behaviours. Simulation is one of the tools to obtain insight in dynamical systems behaviour. Simulation results provide information on performance of system and are helpful in detecting potential weaknesses and errors. Moreover, the results are handy in choosing adequate control strategies and parameters. In our contribution we report a work in progress, a technique for simulation of Behavioural Hybrid Process Calculus, an extension of process algebra that is suitable for the modelling and analysis of hybrid systems. 1

We investigate the problem of specification based testing with dense sets of inputs and outputs, in particular with imprecision as they might occur due to errors in measurements, numerical instability or noisy channels. Using quantitative transition systems to describe implementations and specifications, we introduce implementation relations that capture a notion of correctness “up to ε”, allowing deviations of implementation from the specification of at most ε. These quantitative implementation relations are described as Hausdorff distances between certain sets of traces. They are conservative extensions of the well-known ioco relation. We develop an on-line and an off-line algorithm to generate test cases from a requirement specification, modeled as a quantitative transition system. Both algorithms are shown to be sound and complete with respect to the quantitative implementation relations introduced. Categories and Subject Descriptors

This paper provides a comprehensive introduction to a framework for formal testing using labelled transition systems, based on an extension and reformulation of the ioco theory introduced by Tretmans. We introduce the underlying models needed to specify the requirements, and formalise the notion of test cases. We discuss conformance, and in particular the conformance relation ioco. For this relation we prove several interesting properties, and we provide algorithms to derive test cases (either in batches, or on the fly).