Compilers are central to computing, translating programs written by people into code for machines. Some aspects of compiler development, such as syntax analysis, bridge the theory and the implementation in a principled way, with lexers and parsers being algorithmically derived from high-level specifications. On the other hand, there is currently an unbridged gap between the theoretical specification of a programming language, given by a formal semantics, and the code produced by the compiler. Relating the two post hoc is possible, but difficult and rarely done. However, it doesn't have to be this way. A more principled approach is to begin with a semantics for the language, and seek to derive an implementation that is correct-by-construction. The investigators (Graham Hutton and Dan Ghica) have independently developed two such methodologies, which are based on complementary approaches to semantics (evaluators and abstract machines), but utilise different approaches to syntax (trees and graphs). The aim of this project is to reconcile the two methodologies to develop scalable and reusable frameworks for constructing certified compilers from semantics. The project combines the strengths of two leading research groups, is enhanced by a team of expert collaborators (Patrick Bahr, Mario Lavarez-Picallo, Edwin Brady, Simon Marlow, Anil Madhavapeddy, and Beniamino Accattoli), and is supported by fully-funded PhD studentships from the host departments.

Delivery of audio has become increasingly complex: originally in single channel (mono) or 2-channel stereo format, now surround sound in "5.1" format (5 main speakers plus one low frequency effects channel) is available in many home cinema systems, and many other multichannel audio formats are available (e.g. 6.1, 7.1, 10.2 and 22.2). In addition, new interactive apps allow users to remix musical audio, changing instrument volumes, and music games allow players to control individual instruments. Content creators therefore have to develop new ways to create and distribute their audio content to allow their content to be played back on these multichannel systems, or remixed by users to suit their own tastes. However, much audio content is still in legacy formats, mainly 2-channel stereo. We therefore need ways to "repurpose" this legacy audio content, converting these into surround sound or to the separate "stems" needed for remixable audio. The aim of this project is to develop a new approach to high quality audio repurposing, based on high quality musical audio source separation. To achieve this we will combine new high resolution separation techniques with information such as musical scores, instrument recognition, onset detection, and pitch tracking. Instead of aiming at generic source separation, we will develop algorithms designed to match the separation performance to the final target (upmixing or remixing). In parallel, we will investigate perceptual evaluation measures for source separation, remixing and upmixing, and develop new diagnostic evaluation techniques tailored to measure different aspects of the repurposed outcome. The outcomes of this project will allow music consumers to enjoy their favourite songs in interactive remixing apps and games, even where the original separate "stems" are not available. It will also allow music companies, broadcasters and sound archive holders to provide high quality upmixed versions of their large archive content, for an increasing generation of listeners with surround sound systems in the home.

Modern society faces a fundamental problem: the reliability of complex, evolving software systems on which it critically depends cannot be guaranteed by the established, non-mathematical techniques, such as informal prose specification and ad-hoc testing. Modern companies are moving fast, leaving little time for code analysis and testing; concurrent and distributed programs cannot be adequately assessed via traditional testing methods; users of mobile applications neglect to apply software fixes; and malicious users increasingly exploit programming errors, causing major security disruptions. Trustworthy, reliable software is becoming harder to achieve, whilst new business and cyber-security challenges make it of escalating importance. Developers cope with complexity using abstraction: the breaking up of systems into components and layers connected via software interfaces. These interfaces are described using specifications: for example, documentation in English; test suites with varying degrees of rigour; static typing embedded in programming languages; and formal specifications written in various logics. In computer science, despite widespread agreement on the importance of abstraction, specifications are often seen as an afterthought and a hindrance to software development, and are rarely justified. Formal specification as part of the industrial software design process is in its infancy. My over-arching research vision is to bring scientific, mathematical method to the specification and verification of modern software systems. A fundamental unifying theme of my current work is my unique emphasis on what it means for a formal specification to be appropriate for the task in hand, properly evaluated and useful for real-world applications. Specifications should be validated, with proper evidence that they describe what they should. This validation can come in many forms, from formal verification through systematic testing to precise argumentation that a formal specification accurately captures an English standard. Specifications should be useful, identifying compositional building blocks that are intuitive and helpful to clients both now and in future. Specifications should be just right, providing a clear logical boundary between implementations and client programs. VeTSpec has four related objectives, exploring different strengths of program specification, real-world program library specification and mechanised language specification, in each case determining what it means for the specification to be appropriate, properly evaluated and useful for real-world applications. Objective A: Tractable reasoning about concurrency and distribution is a long-standing, difficult problem. I will develop the fundamental theory for the verified specification of concurrent programs and distributed systems, focussing on safety properties for programs based on primitive atomic commands, safety properties for programs based on more complex atomic transactions used in software transactional memory and distributed databases, and progress properties. Objective B: JavaScript is the most widespread dynamic language, used by 94.8% of websites. Its dynamic nature and complex semantics make it a difficult target for verified specification. I will develop logic-based analysis tools for the specification, verification and testing of JavaScript programs, intertwining theoretical results with properly engineered tool development. Objective C: The mechanised specification of real-world programming languages is well-established. Such specifications are difficult to maintain and their use is not fully explored. I will provide a maintainable mechanised specification of Javascript, together with systematic test generation from this specification. Objective D: I will explore fundamental, conceptual questions associated with the ambitious VeTSpec goal to bring scientific, mathematical method to the specification of modern software systems.

Medical imaging has transformed clinical medicine in the last 40 years. Diagnostic imaging provides the means to probe the structure and function of the human body without having to cut open the body to see disease or injury. Imaging is sensitive to changes associated with the early stages of cancer allowing detection of disease at a sufficient early stage to have a major impact on long-term survival. Combining imaging with therapy delivery and surgery enables 3D imaging to be used for guidance, i.e. minimising harm to surrounding tissue and increasing the likelihood of a successful outcome. The UK has consistently been at the forefront of many of these developments. Despite these advances we still do not know the most basic mechanisms and aetiology of many of the most disabling and dangerous diseases. Cancer survival remains stubbornly low for many of the most common cancers such as lung, head and neck, liver, pancreas. Some of the most distressing neurological disorders such as the dementias, multiple sclerosis, epilepsy and some of the more common brain cancers, still have woefully poor long term cure rates. Imaging is the primary means of diagnosis and for studying disease progression and response to treatment. To fully achieve its potential imaging needs to be coupled with computational modelling of biological function and its relationship to tissue structure at multiple scales. The advent of powerful computing has opened up exciting opportunities to better understand disease initiation and progression and to guide and assess the effectiveness of therapies. Meanwhile novel imaging methods, such as photoacoustics, and combinations of technologies such as simultaneous PET and MRI, have created entirely new ways of looking at healthy function and disturbances to normal function associated with early and late disease progression. It is becoming increasingly clear that a multi-parameter, multi-scale and multi-sensor approach combining advanced sensor design with advanced computational methods in image formation and biological systems modelling is the way forward. The EPSRC Centre for Doctoral Training in Medical Imaging will provide comprehensive and integrative doctoral training in imaging sciences and methods. The programme has a strong focus on new image acquisition technologies, novel data analysis methods and integration with computational modelling. This will be a 4-year PhD programme designed to prepare students for successful careers in academia, industry and the healthcare sector. It comprises an MRes year in which the student will gain core competencies in this rapidly developing field, plus the skills to innovate both with imaging devices and with computational methods. During the PhD (years 2 to 4) the student will undertake an in-depth study of an aspect of medical imaging and its application to healthcare and will seek innovative solutions to challenging problems. Most projects will be strongly multi-disciplinary with a principle supervisor being a computer scientist, physicist, mathematician or engineer, a second supervisor from a clinical or life science background, and an industrial supervisor when required. Each project will lie in the EPSRC's remit. The Centre will comprise 72 students at its peak after 4 years and will be obtaining dedicated space and facilities. The participating departments are strongly supportive of this initiative and will encourage new academic appointees to actively participate in its delivery. The Centre will fill a significant skills gap that has been identified and our graduates will have a major impact in academic research in his area, industrial developments including attracting inward investment and driving forward start-ups, and in advocacy of this important and expanding area of medical engineering.