There are increasing concerns about the safety and security of critical infrastructure such as nuclear power plants, the electricity grid and other utilities in the face of possible cyber attacks. As ageing controllers are replaced by smart devices based on Field-Programmable Gate Arrays (FPGAs) and embedded microprocessors, the safety of such devices raises many concerns. In particular, there is the very real risk of malicious functionality hidden in the silicon or in software binaries, dormant and waiting to be activated. Current hardware and software systems are of such complexity that it is impossible to discover such malicious code through testing. We aim to address this problem by closely connecting the system design specification with the actual implementation through the use of a formal design methodology based on type systems with static and dynamic type checking. The type system will be used as a formal language to encode the design specification so that the actual implementation will automatically be checked against the specification. Static type checking of data types and multiparty session types can ensure the correctness of the interaction between the components. However, as static checking assume full access to the design source code it cannot be used to protect against potential threads issuing from third-party functional blocks (know as ``Intellectual Property Cores'' or IP cores) that are commonly used in hardware design: the provider of the IP core can claim adherence to the types and protocols, so that the IP core will meet the compile-time requirements, but the run-time the behaviour cannot be controlled using static techniques. The same applies to third-party compiled software libraries. Therefore we propose to use run-time checking of data types as well as session types at the boundaries of untrusted modules ("Border Patrol"), so that any intentional or unintentional breach of the specification will safely be intercepted.

Current software development processes are expensive, laborious and error prone. They achieve adaptivity at only a glacial pace, largely through enormous human effort, forcing highly skilled engineers to waste significant time adapting many tedious implementation details. Often, the resulting software is equally inflexible, forcing users to also rely on their innate human adaptivity to find "workarounds". As the letters of support from the DAASE industrial partners demonstrate, this creates a pressing need for greater automation and adaptivity. Suppose we automate large parts of the development process using computational search. Requirements engineering, project planning and testing now become unified into a single automated activity. As requirements change, the project plans and associated tests are adapted to best suit the changes. Now suppose we further embed this adaptivity within the software product itself. Smaller changes to the operating environment can now be handled automatically. Feedback from the operating environment to the development process will also speed adaption of both the software product and process to much larger changes that cannot be handled by such in-situ adaptation. This is the new approach to software engineering DAASE seeks to create. It places computational search at the heart of the processes and products it creates and embeds adaptivity into both. DAASE will also create an array of new processes, methods, techniques and tools for a new kind of software engineering, radically transforming the theory and practice of software engineering. DAASE will develop a hyper-heuristic approach to adaptive automation. A hyper-heuristic is a methodology for selecting or generating heuristics. Most heuristic methods in the literature operate on a search space of potential solutions to a particular problem. However, a hyper-heuristic operates on a search space of heuristics. We do not underestimate the challenges this research agenda poses. However, we believe we have the team, partners and programme plan that will achieve the ambitious aim. DAASE integrates two teams of researchers from the Operational Research and Search Based Software Engineering communities. Both groups of researchers are widely regarded as world leading, having pioneered the fields of Hyper-Heuristics and Search Based Software Engineering (SBSE); the two key fields that DAASE brings together.