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Language Extension via Dynamically Extensible Compilers
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Software used to produce visual beauty is usually created with imperative programming languages and is typically unbeautiful itself. One fundamental reason for this situation is that these languages reflect the underlying discreteness and sequentiality of the computers that run them. The essential nature of what an image is becomes muddled with details of how to display it on a computer. We can, however, generate beautiful images with beautiful programs, by making a shift of programming paradigm, from doing to being. This claim is illustrated by many examples expressed in Pan, an image synthesis language with a freely available optimizing compiler.
Generalised algebraic data types (GADTs), sometimes known as "guarded recursive data types" or "first-class phantom types", are a simple but powerful generalisation of the data types of Haskell and ML. Recent works have given compelling examples of the utility of GADTs, although type inference is known to be difficult. It is time to pluck the fruit. Can GADTs be added to Haskell, without losing type inference, or requiring unacceptably heavy type annotations? Can this be done without completely rewriting the already-complex Haskell type-inference engine, and without complex interactions with (say) type classes? We answer these questions in the affirmative, giving a type system that explains just what type annotations are required, and a prototype implementation that implements it. Our main technical innovation is wobbly types, which express in a declarative way the uncertainty caused by the incremental nature of typical type-inference algorithms.
Standard ML is a general-purpose programming language designed for large projects. This book provides a formal definition of Standard ML for the benefit of all concerned with the language, including users and implementers. Because computer programs are increasingly required to withstand rigorous analysis, it is all the more important that the language in which they are written be defined with full rigor. One purpose of a language definition is to establish a theory of meanings upon which the understanding of particular programs may rest. To properly define a programming language, it is necessary to use some form of notation other than a programming language. Given a concern for rigor, mathematical notation is an obvious choice. The authors have defined their semantic objects in mathematical notation that is completely independent of Standard ML. In defining a language one must also define the rules of evaluation precisely—that is, define what meaning results from evaluating any phrase of the language. The definition thus constitutes a formal specification for an implementation. The authors have developed enough of their theory to give sense to their rules of evaluation. The Definition of Standard ML is the essential point of reference for Standard ML. Since its publication in 1990, the implementation technology of the language has advanced enormously and the number of users has grown. The revised edition includes a number of new features, omits little-used features, and corrects mistakes of definition.
"This book teaches functional programming using Haskell, the most popular purely functional language. The emphasis is on functional programming as a way of thinking and problem solving, using Haskell as a vehicle for expressing solutions. Rather than using conventional examples from mathematics, which are commonly found in other programming language books, this tutorial uses examples drawn from multimedia applications, including graphics, animation, and computer music, thus rewarding the reader with working programs for inherently more interesting applications. The author also teaches how to reason about functional programs, using a very simple process of calculation."--Jacket.
