This article presents a comprehensive examination of model-driven architecture for complex software systems, addressing the critical challenges and opportunities at the intersection of architecture, advanced system architecture, and artificial intelligence. The study synthesizes insights from peer-reviewed references spanning digital twin security, adaptive defense frameworks, deep learning-based anomaly detection, cloud-IoT security management, encrypted search optimization, 5G network security, massive MIMO signal processing, privacy-preserving architectures, and generative model applications. Each reference is individually cited and contextualized within the broader discourse on domain-specific languages, model transformation, code generation, and abstract syntax trees. The article examines how these diverse research contributions collectively inform the design, implementation, and evaluation of robust solutions for contemporary security and architectural challenges. By integrating technical analyses with organizational and practical considerations, this work provides a holistic perspective that is relevant to both researchers and practitioners working to advance the state of the art in architecture.
Tawfik et al. (Sat,) studied this question.
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