Simulationstests

Simulationstests are a testing approach in which a system, component, or process is evaluated within a simulated environment that mirrors key aspects of real-world operation. The method relies on models, data sets, and simulation software to reproduce dynamic behavior, enabling tests to be performed without relying solely on physical prototypes or live deployment.

Common elements include model-based representations of physics, user interactions, or network conditions, along with scenario generation that covers typical and extreme operating cases. In engineering and software contexts, Simulationstests often use techniques such as model-in-the-loop (MIL), software-in-the-loop (SIL), and hardware-in-the-loop (HIL), as well as digital twins and Monte Carlo simulations to explore variability and uncertainty.

Applications span multiple domains. In automotive and aerospace, they are used to validate control systems, safety analyses, and performance under diverse weather or road and flight conditions. Industrial automation and robotics employ Simulationstests to optimize processes and test fault handling. In IT and networks, they support stress testing, capacity planning, and resilience assessment. Regulatory bodies may also require or recognize simulation-based evidence for certification and safety cases.

Benefits include reduced development time and cost, safer testing of dangerous or rare scenarios, and the ability to repeat tests precisely. Limitations arise from the need for accurate models and data, potential gaps between simulation and real-world behavior, and the computational resources required. Effective Simulationstests balance model fidelity with practical testing goals and are typically complemented by selective physical testing to validate results.