Results 1  10
of
119
Comprehending Monads
 Mathematical Structures in Computer Science
, 1992
"... Category theorists invented monads in the 1960's to concisely express certain aspects of universal algebra. Functional programmers invented list comprehensions in the 1970's to concisely express certain programs involving lists. This paper shows how list comprehensions may be generalised to an arbit ..."
Abstract

Cited by 458 (13 self)
 Add to MetaCart
Category theorists invented monads in the 1960's to concisely express certain aspects of universal algebra. Functional programmers invented list comprehensions in the 1970's to concisely express certain programs involving lists. This paper shows how list comprehensions may be generalised to an arbitrary monad, and how the resulting programming feature can concisely express in a pure functional language some programs that manipulate state, handle exceptions, parse text, or invoke continuations. A new solution to the old problem of destructive array update is also presented. No knowledge of category theory is assumed.
How to Make AdHoc Polymorphism Less Ad Hoc
, 1988
"... This paper presents type classes, a new approach to adhoc polymorphism. Type classes permit overloading of arithmetic operators such as multiplication, and generalise the "eqtype variables" of Standard ML. Type classes extend the Hindley/Milner polymorphic type system, and provide a new approach to ..."
Abstract

Cited by 345 (3 self)
 Add to MetaCart
This paper presents type classes, a new approach to adhoc polymorphism. Type classes permit overloading of arithmetic operators such as multiplication, and generalise the "eqtype variables" of Standard ML. Type classes extend the Hindley/Milner polymorphic type system, and provide a new approach to issues that arise in objectoriented programming, bounded type quantification, and abstract data types. This paper provides an informal introduction to type classes, and defines them formally by means of type inference rules. 1 Introduction Strachey chose the adjectives adhoc and parametric to distinguish two varieties of polymorphism [Str67]. Adhoc polymorphism occurs when a function is defined over several different types, acting in a different way for each type. A typical example is overloaded multiplication: the same symbol may be used to denote multiplication of integers (as in 3*3) and multiplication of floating point values (as in 3.14*3.14). Parametric polymorphism occurs wh...
Theorems for free!
 FUNCTIONAL PROGRAMMING LANGUAGES AND COMPUTER ARCHITECTURE
, 1989
"... From the type of a polymorphic function we can derive a theorem that it satisfies. Every function of the same type satisfies the same theorem. This provides a free source of useful theorems, courtesy of Reynolds' abstraction theorem for the polymorphic lambda calculus. ..."
Abstract

Cited by 329 (6 self)
 Add to MetaCart
From the type of a polymorphic function we can derive a theorem that it satisfies. Every function of the same type satisfies the same theorem. This provides a free source of useful theorems, courtesy of Reynolds' abstraction theorem for the polymorphic lambda calculus.
Computational Interpretations of Linear Logic
 Theoretical Computer Science
, 1993
"... We study Girard's Linear Logic from the point of view of giving a concrete computational interpretation of the logic, based on the CurryHoward isomorphism. In the case of Intuitionistic Linear Logic, this leads to a refinement of the lambda calculus, giving finer control over order of evaluation an ..."
Abstract

Cited by 281 (3 self)
 Add to MetaCart
We study Girard's Linear Logic from the point of view of giving a concrete computational interpretation of the logic, based on the CurryHoward isomorphism. In the case of Intuitionistic Linear Logic, this leads to a refinement of the lambda calculus, giving finer control over order of evaluation and storage allocation, while maintaining the logical content of programs as proofs, and computation as cutelimination.
The Lazy Lambda Calculus
 Research Topics in Functional Programming
, 1990
"... Introduction The commonly accepted basis for functional programming is the calculus; and it is folklore that the calculus is the prototypical functional language in puri ed form. But what is the calculus? The syntax is simple and classical; variables, abstraction and application in the pure cal ..."
Abstract

Cited by 239 (3 self)
 Add to MetaCart
Introduction The commonly accepted basis for functional programming is the calculus; and it is folklore that the calculus is the prototypical functional language in puri ed form. But what is the calculus? The syntax is simple and classical; variables, abstraction and application in the pure calculus, with applied calculi obtained by adding constants. The further elaboration of the theory, covering conversion, reduction, theories and models, is laid out in Barendregt's already classical treatise [Bar84]. It is instructive to recall the following crux, which occurs rather early in that work (p. 39): Meaning of terms: rst attempt The meaning of a term is its normal form (if it exists). All terms without normal forms are identi ed. This proposal incorporates such a simple and natural interpretation of the calculus as
Types and persistence in database programming languages
 ACM Computing Surveys
, 1987
"... Databases and have developed one another for Traditionally, the interface between a programming language and a database has either ..."
Abstract

Cited by 157 (2 self)
 Add to MetaCart
Databases and have developed one another for Traditionally, the interface between a programming language and a database has either
Linear Types Can Change the World!
 PROGRAMMING CONCEPTS AND METHODS
, 1990
"... The linear logic of J.Y. Girard suggests a new type system for functional languages, one which supports operations that "change the world". Values belonging to a linear type must be used exactly once: like the world, they cannot be duplicated or destroyed. Such values require no reference counti ..."
Abstract

Cited by 134 (9 self)
 Add to MetaCart
The linear logic of J.Y. Girard suggests a new type system for functional languages, one which supports operations that "change the world". Values belonging to a linear type must be used exactly once: like the world, they cannot be duplicated or destroyed. Such values require no reference counting or garbage collection, and safely admit destructive array update. Linear types extend Schmidt's notion of single threading; provide an alternative to Hudak and Bloss' update analysis; and offer a practical complement to Lafont and HolmstrÃ¶m's elegant linear languages.
Type classes in Haskell
 ACM Transactions on Programming Languages and Systems
, 1996
"... 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 HindleyMilner inference rules. In contrast to other work on type classes, the rules presented here relate directl ..."
Abstract

Cited by 122 (5 self)
 Add to MetaCart
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 HindleyMilner 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 secondorder lambda calculus to record type information in the program. 1.
A Standard ML Compiler
 Functional Programming Languages and Computer Architecture
, 1987
"... Standard ML is a major revision of earlier dialects of the functional language ML. We describe the first compiler written for Standard ML in Standard ML. The compiler incorporates a number of novel features and techniques, and is probably the largest system written to date in Standard ML. Great atte ..."
Abstract

Cited by 93 (14 self)
 Add to MetaCart
Standard ML is a major revision of earlier dialects of the functional language ML. We describe the first compiler written for Standard ML in Standard ML. The compiler incorporates a number of novel features and techniques, and is probably the largest system written to date in Standard ML. Great attention was paid to modularity in the construction of the compiler, leading to a successful largescale test of the modular capabilities of Standard ML. The front end is useful for purposes other than compilation, and the back end is easily retargetable (we have code generators for the VAX and MC68020). The module facilities of Standard ML were taken into account early in the design of the compiler, and they particularly influenced the environment management component of the front end. For example, the symbol table structure is designed for fast access to opened structures. The front end of the compiler is a single phase that integrates parsing, environment management, and type checking. The m...
A Survey Of Stream Processing
, 1995
"... Stream processing is a term that is used widely in the literature to describe a variety of systems. We present an overview of the historical development of stream processing and a detailed discussion of the different languages and techniques for programming with streams that can be found in the lite ..."
Abstract

Cited by 85 (2 self)
 Add to MetaCart
Stream processing is a term that is used widely in the literature to describe a variety of systems. We present an overview of the historical development of stream processing and a detailed discussion of the different languages and techniques for programming with streams that can be found in the literature. This includes an analysis of dataflow, specialized functional and logic programming with streams, reactive systems, signal processing systems, and the use of streams in the design and verification of hardware. The aim of this survey is an analysis of the development of each of these specialized topics to determine if a general theory of stream processing has emerged. As such, we discuss and classify the different classes of stream processing systems found in the literature from the perspective of programming primitives, implementation techniques, and computability issues, including a comparison of the semantic models that are used to formalize stream based computation.