The objective of this project is to research tools to manage uncertainty in the design and certification process of safety-critical aviation systems. The research focuses on three innovative ideas to support this objective. First, probabilistic techniques will be introduced to specify system-level requirements and bound the performance of dynamical components. These will reduce the design costs associated with complex aviation systems consisting of tightly integrated components produced by many independent engineering organizations. Second, a framework will be created for developing software components that use probabilistic execution to model and manage the risk of software failure. These techniques will make software more robust, lower the cost of validating code changes, and allow software quality to be integrated smoothly into overall system-level analysis. Third, techniques from Extreme Value Theory will be applied to develop adaptive verification and validation procedures. This will enable early introduction of new and advanced aviation systems. These systems will initially have restricted capabilities, but these restrictions will be gradually relaxed as justified by continual logging of data from in-service products. The three main research aims will lead to a significant reduction in the costs and time required for fielding new aviation systems. This will enable, for example, the safe and rapid implementation of next generation air traffic control systems that have the potential of tripling airspace capacity with no reduction in safety. The proposed methods are also applicable to other complex systems including smart power grids and automated highways. Integrated into the research is an education plan for developing a highly skilled workforce capable of designing safety critical systems. This plan centers around two main activities: (a) creation of undergraduate labs focusing on safety-critical systems, and (b) integration of safety-critical concepts into a national robotic snowplow competition. These activities will provide inspirational, real-world applications to motivate student learning.

Accurate and reliable knowledge of time is fundamental to cyber-physical systems for sensing, control, performance, and energy efficient integration of computing and communications. This statement underlies the proposal. Emerging CPS applications depend on precise knowledge of time to infer location and control communication. There is a diversity of semantics used to describe time, and quality of time varies as we move up and down the system stack. System designs tend to overcompensate for these uncertainties and the result is systems that may be over designed, inefficient, and fragile. The intellectual merit derives from the new and fundamental concept of time and the holistic measure of quality of time (QoT) that captures metrics including resolution, accuracy, and stability. The proposal builds a system stack ("ROSELINE") that enables new ways for clock hardware, operating system, network services, and applications to learn, maintain and exchange information about time, influence component behavior, and robustly adapt to dynamic QoT requirements, as well as to benign and adversarial changes in operating conditions. Application areas that will benefit from Quality of Time will include: smart grid, networked and coordinated control of aerospace systems, underwater sensing, and industrial automation. The broader impact of the proposal is due to the foundational nature of the work which builds a robust and tunable quality of time that can be applied across a broad spectrum of applications that pervade modern life. The proposal will also provide valuable opportunities to integrate research and education in graduate, undergraduate, and K-12 classrooms. There will be extensive outreach through publications, open sourcing of software, and participation in activities such as the Los Angeles Computing Circle for pre-college students.