This thesis presents and justifies a framework for programming real-time signal processing systems. The framework extends the existing "block-diagram" programming model; it has three components: a very high-level textual language, a visual language, and the dataflow process network model of computation. The dataflow process network model, although widely-used, lacks a formal description, and I provide a semantics for it. The formal work leads into a new form of actor. Having established the semantics of dataflow processes, the functional language Haskell is layered above this model, providing powerful features---notably polymorphism, higher-order functions, and algebraic program transformation---absent in block-diagram systems. A visual equivalent notation for Haskell, Visual Haskell, ensures that this power does not exclude the "intuitive" appeal of visual interfaces; with some intelligent layout and suggestive icons, a Visual Haskell program can be made to look very like a block dia...

Certain classes of applications are naturally described as a network of cooperating components, where each component reacts to input as and when it becomes available. This paper builds on previous work on expressing I/O and state-based algorithms safely in a functional language, and presents a new way of expressing reactive systems in a functional language that does not violate vital semantic properties. The approach taken is a pragmatic one in that it integrates constructs for expressing reactive systems within existing framework for writing I/O bound, statebased programs functionally. The original contributions of this paper are twofold; first, we show how the existing monadic IO model can be extended to cope with nondeterminism, and secondly, we introduce primitives for evaluating I/O actions concurrently. 1 Introduction A large class of applications are naturally described as a collection of components cooperating to solve some task. Examples include operating systems and graphica...

. Persistent programming offers the prospect of seamless integration of programs with long-lived data, offering the prospect of constructing systems that allow more rapid program development, and also simplifying the process of writing applications whose purpose is to handle long-lived data. While there have been some previous attempts to produce persistent functional languages, the majority of these have been interpreted, and performance has generally been seriously compromised. It has therefore become something of a shibboleth that persistence cannot be implemented efficiently in a purely functional language. This paper offers the first systematic study of this claim. This paper describes the first-ever implementation of orthogonal persistence for a compiled purely functional language, based on an existing St Andrews persistent object store. Preliminary performance results show that it is possible to implement orthogonal persistence efficiently and there is hope that the result is mo...

This thesis presents and justi es a framework for programming real-time signal process-ing systems. The framework extends the existing \block-diagram " programming model� it has three components: a very high-level textual language, a visual language, and the data ow process network model of computation. The data ow process network model, although widely-used, lacks a formal description, and I provide a semantics for it. The formal work leads into a new form of actor. Having established the semantics of data ow processes, the functional language Haskell is layered above this model, providing powerful features|notably polymorphism, higher-order func-tions, and algebraic program transformation|absent in block-diagram systems. A visual equivalent notation for Haskell, Visual Haskell, ensures that this power does not exclude the \intuitive " appeal of visual interfaces � with some intelligent layout and suggestive icons, a Visual Haskell program can be made to look very like ablock diagram program. Finally, the functional language is used to further extend data ow process networks, by simulating timed and dynamically-varying networks.