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We show how a set of building blocks can be used to construct programming language interpreters, and present implementations of such building blocks capable of supporting many commonly known features, including simple expressions, three different function call mechanisms (call-by-name, callby -value and lazy evaluation), references and assignment, nondeterminism, first-class continuations, and program tracing. The underlying mechanism of our system is monad transformers, a simple form of abstraction for introducing a wide range of computational behaviors, such as state, I/O, continuations, and exceptions. Our work is significant in the following respects. First, we have succeeded in designing a fully modular interpreter based on monad transformers that includes features missing from Steele's, Espinosa's, and Wadler's earlier efforts. Second, we have found new ways to lift monad operations through monad transformers, in particular difficult cases not achieved in Moggi's original work. ...

Many functions have to be written over and over again for different datatypes, either because datatypes change during the development of programs, or because functions with similar functionality are needed on different datatypes. Examples of such functions are pretty printers, debuggers, equality functions, unifiers, pattern matchers, rewriting functions, etc. Such functions are called polytypic functions. A polytypic function is a function that is defined by induction on the structure of user-defined datatypes. This paper extends a functional language (a subset of Haskell) with a construct for writing polytypic functions. The extended language type checks definitions of polytypic functions, and infers the types of all other expressions using an extension of Jones ' theories of qualified types and higher-order polymorphism. The semantics of the programs in the extended language is obtained by adding type arguments to functions in a dictionary passing style. Programs in the extended language are translated to Haskell. 1

Type classes in Haskell allow programmers to define functions that can be used on a set of different types, with a potentially different implementation in each case. For example, type classes are used to support equality and numeric types, and for monadic programming. A commonly requested extension to support ‘multiple parameters ’ allows a more general interpretation of classes as relations on types, and has many potentially useful applications. Unfortunately, many of these examples do not work well in practice, leading to ambiguities and inaccuracies in inferred types and delaying the detection of type errors. This paper illustrates the kind of problems that can occur with multiple parameter type classes, and explains how they can be resolved by allowing programmers to specify explicit dependencies between the parameters. A particular novelty of this paper is the application of ideas from the theory of relational databases to the design of type systems.

This paper de nes a set of type inference rules for resolving overloading introduced by type classes. Programs including type classes are transformed into ones which may be typed by the Hindley-Milner inference rules. In contrast to other work on type classes, the rules presented here relate directly to user programs. An innovative aspect of this work is the use of second-order lambda calculus to record type information in the program. 1.

How canweintegrate interaction into a purely declarative language? This tutorial describes a solution to this problem based on a monad. The solution has been implemented in the functional language Haskell and the declarative language Escher. Comparisons are given to other approaches to interaction based on synchronous streams, continuations, linear logic, and side effects.

Fold and unfold are general purpose functionals for processing and constructing lists. By using the categorical approach of modelling recursive datatypes as fixed points of functors, these functionals and their algebraic properties were generalised from lists to polynomial (sum-of-product) datatypes. However, the restriction to polynomial datatypes is a serious limitation: it precludes the use of exponentials (functionspaces) , whereas it is central to functional programming that functions are first-class values, and so exponentials should be able to be used freely in datatype definitions. In this paper we explain how Freyd's work on modelling recursive datatypes as fixed points of difunctors shows how to generalise fold and unfold from polynomial datatypes to those involving exponentials. Knowledge of category theory is not required; we use Gofer throughout as our meta-language, making extensive use of constructor classes. 1 Introduction During the 1980s, Bird and Meertens [6, 22] d...

This paper describes a new approach to generic functional programming, which allows us to define functions generically for all datatypes expressible in Haskell. A generic function is one that is defined by induction on the structure of types. Typical examples include pretty printers, parsers, and comparison functions. The advanced type system of Haskell presents a real challenge: datatypes may be parameterized not only by types but also by type constructors, type definitions may involve mutual recursion, and recursive calls of type constructors can be arbitrarily nested. We show that--- despite this complexity---a generic function is uniquely defined by giving cases for primitive types and type constructors (such as disjoint unions and cartesian products). Given this information a generic function can be specialized to arbitrary Haskell datatypes. The key idea of the approach is to model types by terms of the simply typed -calculus augmented by a family of recursion operators. While co...

The Hindley/Milner type system has been widely adopted as a basis for statically typed functional languages. One of the main reasons for this is that it provides an elegant compromise between flexibility, allowing a single value to be used in different ways, and practicality, freeing the programmer from the need to supply explicit type information. Focusing on practical applications rather than implementation or theoretical details, these notes examine a range of extensions that provide more flexible type systems while retaining many of the properties that have made the original Hindley/Milner system so popular. The topics discussed, some old, but most quite recent, include higher-order polymorphism and type and constructor class overloading. Particular emphasis is placed on the use of these features to promote modularity and reusability.

Monads are becoming an increasingly important tool for functional programming. Different monads can be used to model a wide range of programming language features. However, real programs typically require a combination of different features, so it is important to have techniques for combining several features in a single monad. In practice, it is usually possible to construct a monad that supports some specific combination of features. However, the techniques used are typically ad-hoc and it is very difficult to find general techniques for combining arbitrary monads. This report gives three general constructions for the composition of monads, each of which depends on the existence of an auxiliary function linking the monad structures of the components. In each case, we establish a set of laws that the auxiliary function must satisfy to ensure that the composition is itself a monad. Using the notation of constructor classes, we describe some specific applications of these constructions. These results are used in the development of a simple expression evaluator that combines exceptions, output and an environment of variable bindings using a composition of three corresponding monads. 1