Ricarda Schüssler

• The rapid growth of systems, both in size and complexity, combined with their distributed nature, is posing challenges for their efficient integration and functioning. Moreover, in order to achieve sustainability objectives and future goals, systems are increasingly collaborating with each other, resulting in the emergence of Systems of Systems (SoS) that are large-scale and independent. In such scenarios, multiple stakeholders and systems from different disciplines with diverse interests need to interoperate. In various domains, this trend of growing systems creates a greater need for interfaces that ensure seamless interoperability in between and within these systems and SoS. To address these challenges, an effective method for integrating systems and SoS is required. A key to ease this integration can be the use of interface specifications to describe and specify interfaces. However, there is currently no comprehensive understanding of how to write high-quality interface specifications, nor is there a common overview of interface specification approaches. This thesis aims to fill these gaps of documented knowledge by reviewing recent developments and best practices for interface specifications in the context of systems engineering and SoS engineering. The review was conducted through a literature review focusing on interface specifications, complemented by an analysis of existing interface specification approaches and expert interviews. The goal is to provide an overview of current interface specification characteristics and their common use cases. Based on this analysis, a usage-driven approach in the form of customised interface specification mappings was developed, which can assist in identifying an appropriate approach for specifying interfaces. In light of the increasing connectivity in our lives, the work provides a framework for better classifying and approaching interface specifications, seeking to move away from viewing interfaces as neglected elements of systems engineering, towards a more intelligent and productive classification and approach.