Digital twins have emerged as a powerful technology for modeling and simulating complex systems across various domains (Fuller et al., 2020; Tao et al., 2019). As virtual representations of physical assets, processes, or systems, digital twins enable real-time monitoring, predictive analysis, and optimization. However, as digital twins become more sophisticated and integral to decision-making processes, ensuring their accuracy, reliability, and ethical implementation is essential. This paper presents a comprehensive framework for the Testing, Evaluation, Verification and Validation (TEVV) of digital twins to address the unique challenges posed by these dynamic and complex virtual models.
@article{arxiv.2507.04555,
title = {Testing, Evaluation, Verification and Validation (TEVV) of Digital Twins: A Comprehensive Framework},
author = {Gabriella Waters},
journal= {arXiv preprint arXiv:2507.04555},
year = {2025}
}