Abstract

This paper proposes a Python-based infrastructure for studying the characteristics and behavior of families of systems. The infrastructure allows automatic execution of simulation experiments with varying system structures as well as with varying parameter sets in different simulators. Possible system structures and parameterizations are defined using a System Entity Structure (SES). The SES is a high level approach for variability modeling, particularly in simulation engineering. An SES describes a set of system con1gurations, i.e. different system structures and parameter settings of system components. In combination with a Model Base (MB), executable models can be generated from an SES. Based on an extended SES/MB approach, an enhanced software framework is introduced that supports variability modeling and automatic model generation for different simulation environments. By means of an engineering application it is shown, how a set of Python-based open source software tools can be used to model an SES and to automatically generate and execute signal-flow oriented models.