Recent decades saw the complexity of modern engineered systems raise to never-before seen heights. Developments such as Smart Grids, the Internet-of-Things, Cyber-Physical Systems and Machine Learning open new opportunities, but also pose new challenges for systems engineers who have to integrate and navigate through a highly diverse network of application and computation nodes. Ranging from huge cloud services to powerful edge devices such as autonomous vehicles, systems creators at simultaneously have to choose how to build, structure, maintain and certify their systems’ functionality. After all, non-functioning cloud services might impact the lives of millions of users and involve enormous financial loss, while bringing highly autonomous agents (e.g. self-driving vehicles or delivery robots) and consumer health applications (e.g. pacemakers) have the potential to severely threaten human safety, health and life, if mismanaged.

The systems modelling and engineering community is at the forefront of developing solutions to manage this complexity. Models provide means to abstract over details, at different levels, and interact with specific “system views”. Having created tools and formalisms to design and analyse such systems, the recent rise in complexity also affects this domain. Starting from the conceptualisation of Multi-paradigm Modelling (MPM) [1], which proposes to “model every part and aspect of a system explicitly, using the most appropriate modelling formalism(s) at the most appropriate level(s) of abstraction”, this multiplicity is nowadays expanded to various other parts of the modelling discipline.

Modern systems typically require the management and synchronisation of many system views [2], where each stakeholder may require many different perspectives of a system. These views further impose different levels of abstraction [3] using different modelling formalisms, to be effective. In addition to this complexity aspect, especially in large physical systems and systems-of-systems, the use of different abstraction levels introduces the need for dealing with different levels of fidelity [4] as with growing abstraction levels the necessary lack of details can be modelled as uncertainty [5]. In concert, these multiplicities (i.e. multi-* aspects such as multi-paradigm, multi-view, multi-abstraction, multi-fidelity, etc) require careful consideration, demanding sophisticated approaches, well-defined methodologies and the development of new modelling techniques and tools that support researchers and practitioners in the development of the next generation of large and complex systems. This requires the combination of various approaches ranging from classical formal methods and abstraction to the development of novel methods that include (but are not limited to) probabilistic fidelity and uncertainty modelling, surrogate modelling and substitutability, model adaptability and evolution, as well as the incorporation of AI to foster model understandability and explainability.

This meeting will bring together systems modelling, engineering and formal methods experts from academia and industry, featuring and taking a special focus on the complexity of modern systems engineering, to discuss how to design new engineering practices, especially for complex systems. Our goal is to deepen the understanding of the different kinds of multiplicities that modern systems engineering and systems modelling including multi-stakeholder, multi-domain, multi-formalism, multi-abstraction, multi-view and multi-fidelity modelling, learn from one another and develop a practical skill set to apply in the next generation of complex systems. Systems modelling covers a vast domain, ranging from the model-based systems engineering to formal modelling and verification, to model-driven DevOps processes, where each sub-community discovers novel techniques for their domain problems. The objective is to think out of the box and come up with a coherent vision for research on systems engineering in the next decades.

The meeting we propose is a great opportunity to gather world-leading researchers and industry practitioners who pushed the forefront of the state-of-the-art and achieved new results over the past few years, so that we could further exchange novel ideas and techniques, learn from one another, and promote this truly important research direction and its industrial applications, together conquering the currently urgent demand of managing the multiplicities of modern systems.

There have been several Shonan meetings that focused on the modelling of cyber-physical systems, mainly from the formal methods community. Our unique and significant focus is on extending the current modelling knowledge to multiplicities such as multi-domain, multi-formalism, multi-abstraction, multi-view and multi-fidelity, which is essential to tackle the increasing complexity without restricting the discussion to fully formal (mathematical) models.

• #48: Integration of Formal Methods and Testing for Model-based Systems Engineering

• #55: Science and Practice of Engineering Trustworthy Cyber-Physical Systems (TCPS)
• #118: Modelling and Analysing Resilient Cyber-Physical Systems
• #121: Towards industrial application of advanced formal methods for cyber-physical system engineering
• #124: Model-Based Design for Smart Products and Systems: Advanced Capabilities and Challenging Applications

The meeting will have three types of sessions. The first type of session will have short presentations where selected participants will introduce the latest development of the state-of-the-art of a specific subdomain, and propose ideas/challenges/research directions to be discussed during the meeting. Such presentations will be scheduled during the first day of the meeting. The second type of session will consist in intensive discussions among sub-groups of participants. The topics of the discussions will be decided at the meeting among those proposed by participants during their short talks. The organisers will prepare beforehand some possible topics of discussion, in consultation with participants. The discussions will proceed in three phases, by first exploring different topics, then deepening on a restricted set of selected topics, followed by a synthesis phase.

[1] Vangheluwe, Hans, et al. "An introduction to multi-paradigm modelling and simulation." Proc. Conference on AI, Simulation and Planning in High Autonomy Systems. 2002.

[2] Jörg Kienzle, et al. “Aspect-oriented multi-view modeling”. Proc. Aspect-Oriented Software Development 2009.

[3] Vanherpen, Ken, et al. "Ontological reasoning for consistency in the design of cyber-physical systems." Proc. Int. Workshop on Cyber-Physical Production Systems, 2016.

[4] Seon Han Choi, et al. “Multi-fidelity modeling & simulation methodology for simulation speed up”. Proc SIGSIM PAD 2014.

[5] Troya, Javier, et al. "Uncertainty representation in software models: a survey." Software and Systems Modeling 20(4). 2021.