The relentless growth of complexity and heterogeneity of CPS and IoT systems imposes major challenges and offers new opportunities for design automation methods and tools. Intrinsic heterogeneity—the large span in size from small CPS appliances to societal-scale systems—enabled by IoT devices and the complex interaction among computational, physical, and human components makes the development of design automation tools necessary but very difficult. One hard challenge in automating heterogeneous CPS and IoT design flows is that they crosscut several discipline-oriented design verticals. Their integration requires new co-design methods, horizontal integration platforms for domain-specific models and tools, and the incorporation of data analytics tools for advancing the fusion of model- and data-driven design methodologies.

In addition, incorporation of Learning Enabled Components (LEC) in CPS and IoT architectures leads to new challenges in design flows that require re-thinking the fundamentals of assurance and certification. This trend drives the need for tighter integration of design-time methods and tools into operation. In the new generation of evolving, self-adaptive CPS and IoT, critical system properties must be ensured at design time as well as at run time.  

These challenges are complemented by new opportunities offered by the incorporation of AI-based co-design tools in design flows. Formal modeling, synthesis, and verification tools are extended with methods for adaptive exploration of design spaces, discovering useful patterns in system architectures, and auto-generating details based on learned design rules.