# MBSE Testbed for Rapid, Cost-Effective Prototyping and Evaluation of System Modeling Approaches
## 3 Results
### MBSE Testbed Concept  
The MBSE testbed concept is broader than that of conventional hardware-in-the-loop (HWIL) testbeds. HWIL testbeds are used for early integration and testing of physical systems as well as formal verification and validation (V&V). Typical HWIL testbeds consist of hardware, software modules, and simulations in which system components are either physically present or simulated. Simulated components are progressively replaced by physical components as they become available [10]. The MBSE testbed construct extends HWIL capabilities by including the means for developing and exercising abstract models independently or interoperating with HWIL [11; 12; 13; 14; 15]. Just as importantly, the MBSE testbed construct provides a modeling, simulation, and integration environment for developing and evaluating digital twins [5]. The envisioned capabilities of the MBSE testbed include the ability to:  
* _represent models at multiple scales_ and from different perspectives. * _integrate with digital twins_ of physical systems--support both symbolic and high fidelity, time-accurate simulations; the latter can be augmented by FPGA-based development boards to create complex, time-critical simulations; and maintain synchronization between real-world hardware and virtual simulation. * _accommodate multiple views_, multiple models, analysis tools, learning algorithms. * _manage dynamically configurable systems_ through software agents, employed in the simulation--in the future these agents could invoke processes allocated to Field Programmable Gate Arrays (FPGAs). * _compose interoperable systems_ with requisite flexibility to satisfy mission needs [10; 16]
* _collect and generate evidence_ for developing trust in systems. * _exploit feedback_ from the system and environment during adaptive system operation. * _address temporal constraints_ and their time-related considerations. * _address change cascades_ (e.g., arising from failures) not addressed by existing tools. * _validate models_, which implies flexibility in simulation interfaces as well as propagation of changes in modeled components as data are collected in physical tests. The testbed offers a means to improve understanding of functional requirements and operational behavior of the system in a simulated environment. It provides measurements from which quantitative characteristics of the system can be derived. It provides an implementation laboratory environment in which modeled real-world systems (i.e., digital twins) can be evaluated from different perspectives. A testbed, in essence, comprises three components: an experimentation subsystem; a monitoring and measurement system; and a simulation-stimulation subsystem. The experimentation subsystem comprises real-world system components and prototypes which are the subject of experimentation. The monitoring and measurement system comprises interfaces to the experimentation system to extract raw data and a support component to collate and analyze the collected information. The simulation-stimulation subsystem provides the hooks and handles to experiment with real-world system agents and outputs to ensure a realistic experimentation environment. However, testbeds can have limitations. For example, they cost too much, and they are limited to modeling systems and components that satisfy the testbed environment constraints. In addition, for some problems, analytic and/or simulation models may be more appropriate. This would be the case for complex distributed systems. Therefore, testbeds can be viewed as a flexible and modeler platform that complements/subsumes simulation and analytic methods. Figure 1 presents the MBSE testbed concept.