This paper is a further step towards application of the Model-Based Systems Engineering (MBSE) paradigm, using standardized, graphical, and executable system modeling languages. It presents further development of Modelica graphical Modeling Language (ModelicaML), a UML Profile for Modelica, which enables an integrated modeling and simulation of system requirements and design (for systems including both hardware and software). This approach combines the power of the OMG UML/SysML standardized graphical notation for system and software modeling, and the modeling and simulation power of Modelica. It facilitates the creation of executable system-specification and analysis models that can simulate time-discrete (or eventbased) and time-continuous system behavior.

OpenModelica is a unique large-scale integrated open-source Modelica-and FMI-based modeling, simulation, optimization, model-based analysis and development environment. Moreover, the OpenModelica environment provides a number of facilities such as debugging; optimization; visualization and 3D animation; web-based model editing and simulation; scripting from Modelica, Python, Julia, and Matlab; efficient simulation and co-simulation of FMI-based models; compilation for embedded systems; Modelica-UML integration; requirement verification; and generation of parallel code for multi-core architectures. The environment is based on the equation-based object-oriented Modelica language and currently uses the MetaModelica extended version of Modelica for its model compiler implementation. This overview paper gives an up-to-date description of the capabilities of the system, short overviews of used open source symbolic and numeric algorithms with pointers to published literature, tool integration aspects, some lessons learned, and the main vision behind its development.

OpenModelica is currently the most complete opensource Modelica-and FMI-based modeling, simulation, optimization, and model-based development environment. Moreover, the OpenModelica environment provides a number of facilities such as debugging; optimization; visualization and 3D animation; web-based model editing and simulation; scripting from Modelica, Python, Julia, and Matlab; efficient simulation and co-simulation of FMI-based models; compilation for embedded systems; Modelica-UML integration; requirement verification; and generation of parallel code for multi-ore architectures. The environment is based on Modelica and uses an extended version of Modelica for its implementation. This overview paper intends to give an up-to-date brief description of the capabilities of the system, and the main vision behind its development.

Abstract.This paper provides an overview of the formal transformation between the two complementary languages: OMG SysML TM and Modelica. SysML is a standardized general purpose graphical modeling language for capturing complex system descriptions in terms of their structure, behavior, properties, and requirements. Modelica is a standardized general purpose systems modeling language for analyzing the continuous and discrete time dynamics of complex systems in terms of differential algebraic equations. Integrating the descriptive power of SysML models with the analytic and computational power of Modelica models provides a capability that is significantly greater than provided by SysML or Modelica individually. A standardized bi-directional transformation between the two modeling languages is being developed that will support implementations to transfer efficiently and automatically the modeling information between SysML and Modelica models without ambiguity. In addition to an overview of this bi-directional transformation approach, the paper provides a simple example to clarify the transformation principles and to illustrate the important synergies resulting from the integration between these two languages.

Autonomous systems are on the rise. However, the challenge to test autonomous systems to ensure their safe and fault‐free behaviour is not solved yet. This is especially critical when we consider the fact that autonomous systems are often safety‐critical systems envisaged to interact with humans without explicit human supervision. This paper points out why testing autonomous systems is such a challenge and provides an overview of the current state‐of‐the‐art theory and practice. The gathered information is then condensed into guiding points for the way forward.