An Automated Verification Framework for DEVS-Coupled Models to Enhance Efficient Modeling and Simulation

Discrete Event System Specification (DEVS) is a formalism widely used for modeling and simulating complex systems. The main features of DEVS are defining models in a strict mathematical form and representing systems through hierarchical structures. However, when DEVS models have incorrect connection structures and inappropriate behaviors contrary to design intentions, simulation results can be distorted. This can cause serious problems that may lead to inaccurate decision-making. In this paper, we propose an automated verification framework to improve the accuracy and efficiency of coupled models in the DEVS-Python environment. This framework defines test scripts for coupled models, performs automatic verification before simulation execution, and provides the results to users. Experimental results showed that the proposed framework improved execution time by approximately 30–100 times compared to traditional unit testing methods, although memory and CPU usage increased slightly. Despite this increase in resource usage, the proposed framework provides high efficiency and consistent performance in verifying complex DEVS-coupled models.