This paper introduces design contracts between control and embedded software engineers for building Cyber-Physical Systems (CPS). CPS design involves a variety of disciplines mastered by teams of engineers with diverse backgrounds. Many system properties influence the design in more than one discipline. The lack of clearly defined interfaces between disciplines burdens the interaction and collaboration. We show how design contracts can facilitate interaction between 2 groups: control and software engineers. A design contract is an agreement on certain properties of the system. Every party specifies requirements and assumptions on the system and the environment. This contract is the central point of interdomain communication and negotiation. Designs can evolve independently if all parties agree to a contract or designs can be modified iteratively in negotiation processes. The main challenge lies in the definition of a concise but sufficient contract. We discuss design contracts that specify timing and functionality, two important properties control and software engineers have to agree upon. Various design approaches have been established and implemented successfully to address timing and functionality. We formulate those approaches as design contracts and propose guidelines on how to choose, derive and employ them. Modeling and simulation support for the design contracts is discussed using an illustrative example.
Abstract-One of the biggest challenges in cyber-physical system (CPS) design is their intrinsic complexity, heterogeneity, and multidisciplinary nature. Emerging distributed CPS integrate a wide range of heterogeneous aspects such as physical dynamics, control, machine learning, and error handling. Furthermore, system components are often distributed over multiple physical locations, hardware platforms and communication networks. While model-based design (MBD) has tremendously improved the design process, CPS design remains a difficult task. Models are meant to improve understanding of a system, yet this quality is often lost when models become too complicated. In this paper, we show how to use aspect-oriented (AO) modeling techniques in MBD as a systematic way to segregate domains of expertise and cross-cutting concerns within the model. We demonstrate these concepts on actor-oriented models of an industrial robotic swarm application and illustrate the use of AO modeling techniques to manage the complexity. We also show how to use AO modeling for design-space exploration.
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