The first decade of CPS research has inspired convergence among disciplines in computer science and physical sciences, particularly in areas focusing on foundations for engineered systems. This convergence is driven by a broad cross-disciplinary research community engaged in developing new foundations for complex CPS enabled by emerging platforms such as Industrial Internet (II), Internet of Things (IoT) and Industrie 4.0. The ongoing cross-disciplinary synthesis unavoidably produces clashes among established views, biases and approaches – with the potential benefit that their resolution may yield new insights.

The goal of this workshop is to identify and document game changing, but possibly controversial topics with the purpose of stimulating discussions in the research community. For example, improving scalability of verification methods by selecting the appropriate level of abstraction is an effective approach in computing. However, in modeling physical systems, the selected abstractions influence the epistemic gap between the model and the physical reality. How can we reconcile this problem in verifying CPS? What is better: loss of scalability or loss of validity?

There are many similar problems that may or may not have resolution, such as

  • model-based and model-free approaches,
  • the role of non-determinism in CPS modeling,
  • modeling physical and epistemic uncertainties,
  • the explicit use of time in modeling computations,
  • the limits of compositionality and tradeoffs between compositionality and performance,
  • impact of learning on verifiability – and many other potential topics.

Discussions at the workshop will focus on articulating the topics, presenting conflicting views and assessing the importance of their resolutions. Workshop participants will be asked to posit challenges, take positions – but without the intention of resolving the conflicts.