Cyber-Physical Systems (CPS) are software-controlled systems that have complex interactions with the physical world. Many CPS, such as autonomous drones and self-driving cars, are becoming increasingly more embedded in our society, and therefore safety-critical and demanding of rigorous quality assurance. To this end, CPS engineering relies on modeling methods from diverse scientific and engineering fields, for example control theory and real-time scheduling. Diverse modeling methods are difficult to combine with each other due to their complexity and heterogeneity. Inconsistencies between models and analyses that come from different modeling methods often lead to implicit design errors, which subsequently can cause critical CPS failures with loss of lives and substantial material resources.
To detect and prevent inconsistencies between CPS modeling methods, this thesis investigates an improved architectural approach to integration of CPS modeling methods. This approach relies on architectural views (annotated component-and-connector models) to abstract out and check integration-relevant information from detailed models (e.g., hybrid programs). On top of these views I introduce a novel integration perspective based analyses -- algorithms and procedures that interpret and augment models. For each analysis I propose to specify a contract that captures inputs, outputs, assumptions and guarantees of the analysis in terms of view elements. A particularly challenging task is creating a language to express assumptions, guarantees, and consistency statements over heterogeneous models and views. This language needs to strike a balance between expressiveness and decidability to be effective in the CPS context.
The conceptual advances of this thesis enable a new level of automation for CPS modeling method integration. I will implement these advances in a toolset that will support automated model-view synchronization, analysis execution, and verification of semantic consistency between models. This toolset will serve as a means of evaluating the proposed integration approach in case studies of realistic CPS systems, such as autonomous spacecraft and collaborative robots. I will validate claims about correctness, effectiveness, and generality of my approach.
David Garlan (Chair, ISR)
André Platzer (CSD CMU)
Bruce Krogh (ECE CMU)
Dionisio de Niz (Software Engineering Institute, CMU)
John Day (Jet Propulsion Laboratory/NASA)