# MBSE Testbed for Rapid, Cost-Effective Prototyping and Evaluation of System Modeling Approaches
## 3 Results
### MBSE Testbed Concept
The testbed comprises a user interface that supports the following: scenario authoring, dashboard capabilities for scenario execution monitoring visualization, and control, and report generation; a suite of modeling and analysis tools including system modelers, machine learning and data analytics algorithms; simulation engines for discrete event simulation, hybrid simulation, and component simulation; and repositories of operational scenario vignettes, system models, component libraries, and experimentation results. The testbed supports system conceptualization, realization, and assurance. _System conceptualization_ comprises use case development; requirement elicitation, decomposition, and allocation; system concept of operations (CONOPS); logical architectures; metrics; initial system models; and initial validation concepts. _System realization_ entails detailed design, physical and simulation development, and integration and test. _System assurance_ comprises evaluating system safety, security, and mission assurance. Complex systems are invariably a combination of third-party components and legacy components from previously deployed systems. As such, some components tend to be fully verified under certain operating conditions that may or may not apply in their reuse. Furthermore, complex systems are subject to unreliable interactions (e.g., sporadic or incorrect sensor inputs, and control commands that are not always precisely followed) because they interact frequently with the physical world. Finally, with increasing connectedness, they are increasingly susceptible to security threats. In light of the foregoing, the MBSE testbed needs to provide:  
* _Interitance evaluation_, in which legacy and third-party components are subjected to the usage and environmental conditions of the new system. * _Probabilistic learning models_, which begin with incomplete system representations and progressively fill in details and gaps with incoming data from collection assets; the latter enable learning and filling in gaps in the knowledge of system and environment states. * _Networked control_, which requires reliable execution and communication that enables satisfaction of hard time deadlines [5,17] across a network. Because networked control is susceptible to multiple points of cyber vulnerabilities, the testbed infrastructure should incorporate cybersecurity and cyber-resilience. * _Entforceable properties_ define core attributes of a system that must remain immutable in the presence of dynamic and potentially unpredictable environments. The testbed must support verification that these properties are dependable regardless of external conditions and changes. * _Commercial off-the-shelf (COTS) components_, which typically communicate with each other across multiple networks and time scales [5,18]. The latter requires validation of interoperability among COTS systems. * _Support for safety-critical_ systems in the form of, for example, executable, real-time system models that detect safety problems and then shut down the simulation, while the testbed can be queried to determine what happened. Figure 1: Model-based systems engineering (MBSE) testbed concept.