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A New Approach to Generic Functional Programming
 In The 27th Annual ACM SIGPLANSIGACT Symposium on Principles of Programming Languages
, 1999
"... 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 co ..."
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Cited by 99 (13 self)
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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 complexitya 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...
Bananas in Space: Extending Fold and Unfold to Exponential Types
, 1995
"... 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 (sumofproduct) datatypes ..."
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Cited by 98 (6 self)
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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 (sumofproduct) 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 firstclass 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 metalanguage, making extensive use of constructor classes. 1 Introduction During the 1980s, Bird and Meertens [6, 22] d...
Polytypic programming
, 2000
"... ... PolyP extends a functional language (a subset of Haskell) with a construct for defining polytypic functions by induction on the structure of userdefined datatypes. Programs in the extended language are translated to Haskell. PolyLib contains powerful structured recursion operators like catamorp ..."
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Cited by 95 (11 self)
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... PolyP extends a functional language (a subset of Haskell) with a construct for defining polytypic functions by induction on the structure of userdefined datatypes. Programs in the extended language are translated to Haskell. PolyLib contains powerful structured recursion operators like catamorphisms, maps and traversals, as well as polytypic versions of a number of standard functions from functional programming: sum, length, zip, (==), (6), etc. Both the specification of the library and a PolyP implementation are presented.
Nested datatypes
 In MPC’98, volume 1422 of LNCS
, 1998
"... Abstract. A nested datatype, also known as a nonregular datatype, is a parametrised datatype whose declaration involves different instances of the accompanying type parameters. Nested datatypes have been mostly ignored in functional programming until recently, but they are turning out to be both th ..."
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Cited by 90 (6 self)
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Abstract. A nested datatype, also known as a nonregular datatype, is a parametrised datatype whose declaration involves different instances of the accompanying type parameters. Nested datatypes have been mostly ignored in functional programming until recently, but they are turning out to be both theoretically important and useful in practice. The aim of this paper is to suggest a functorial semantics for such datatypes, with an associated calculational theory that mirrors and extends the standard theory for regular datatypes. Though elegant and generic, the proposed approach appears more limited than one would like, and some of the limitations are discussed. 1
Generic Haskell: practice and theory
 In Generic Programming, Advanced Lectures, volume 2793 of LNCS
, 2003
"... Abstract. Generic Haskell is an extension of Haskell that supports the construction of generic programs. These lecture notes describe the basic constructs of Generic Haskell and highlight the underlying theory. Generic programming aims at making programming more effective by making it more general. ..."
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Cited by 72 (23 self)
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Abstract. Generic Haskell is an extension of Haskell that supports the construction of generic programs. These lecture notes describe the basic constructs of Generic Haskell and highlight the underlying theory. Generic programming aims at making programming more effective by making it more general. Generic programs often embody nontraditional kinds of polymorphism. Generic Haskell is an extension of Haskell [38] that supports the construction of generic programs. Generic Haskell adds to Haskell the notion of structural polymorphism, the ability to define a function (or a type) by induction on the structure of types. Such a function is generic in the sense that it works not only for a specific type but for a whole class of types. Typical examples include equality, parsing and pretty printing, serialising, ordering, hashing, and so on. The lecture notes on Generic Haskell are organized into two parts. This first part motivates the need for genericity, describes the basic constructs of Generic Haskell, puts Generic Haskell into perspective, and highlights the underlying theory. The second part entitled “Generic Haskell: applications ” delves deeper into the language discussing three nontrivial applications of Generic Haskell: generic dictionaries, compressing XML documents, and a generic version of the zipper data type. The first part is organized as follows. Section 1 provides some background discussing type systems in general and the type system of Haskell in particular. Furthermore, it motivates the basic constructs of Generic Haskell. Section 2 takes a closer look at generic definitions and shows how to define some popular generic functions. Section 3 highlights the theory underlying Generic Haskell and discusses its implementation. Section 4 concludes. 1
Generalised Folds for Nested Datatypes
 Formal Aspects of Computing
, 1999
"... Nested datatypes generalise regular datatypes in much the same way that contextfree languages generalise regular ones. Although the categorical semantics of nested types turns out to be similar to the regular case, the fold functions are more limited because they can only describe natural transform ..."
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Cited by 44 (1 self)
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Nested datatypes generalise regular datatypes in much the same way that contextfree languages generalise regular ones. Although the categorical semantics of nested types turns out to be similar to the regular case, the fold functions are more limited because they can only describe natural transformations. Practical considerations therefore dictate the introduction of a generalised fold function in which this limitation can be overcome. In the paper we show how to construct generalised folds systematically for each nested datatype, and show that they possess a uniqueness property analogous to that of ordinary folds. As a consequence, generalised folds satisfy fusion properties similar to those developed for regular datatypes. Such properties form the core of an effective calculational theory of inductive datatypes.
Calculate Polytypically!
 In PLILP'96, volume 1140 of LNCS
, 1996
"... A polytypic function definition is a function definition that is parametrised with a datatype. It embraces a class of algorithms. As an example we define a simple polytypic "crush" combinator that can be used to calculate polytypically. The ability to define functions polytypically adds an ..."
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Cited by 41 (3 self)
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A polytypic function definition is a function definition that is parametrised with a datatype. It embraces a class of algorithms. As an example we define a simple polytypic "crush" combinator that can be used to calculate polytypically. The ability to define functions polytypically adds another level of flexibility in the reusability of programming idioms and in the design of libraries of interoperable components.
A Generic Programming Extension for Haskell
 Utrecht University
, 1999
"... Many functions can be dened completely generically for all datatypes. Examples include pretty printers (eg show), parsers (eg read), data converters, equality and comparison functions, mapping functions, and so forth. This paper proposes a generic programming extension that enables the user to dene ..."
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Cited by 41 (4 self)
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Many functions can be dened completely generically for all datatypes. Examples include pretty printers (eg show), parsers (eg read), data converters, equality and comparison functions, mapping functions, and so forth. This paper proposes a generic programming extension that enables the user to dene such functions in Haskell. In particular, the proposal aims at generalizing Haskell's deriving construct, which is commonly considered decient since instance declarations can only be derived for a few predened classes. Using generic denitions derived instances can be specied for arbitrary userdened type classes and for classes that abstract over type constructors of rstorder kind. 1 Introduction Generic or polytypic programming aims at relieving the programmer from repeatedly writing functions of similar functionality for dierent datatypes. Typical examples for socalled generic functions include pretty printers (eg show), parsers (eg read), functions that convert data into a u...
Tupling Calculation Eliminates Multiple Data Traversals
 In ACM SIGPLAN International Conference on Functional Programming
, 1997
"... Tupling is a wellknown transformation tactic to obtain new efficient recursive functions by grouping some recursive functions into a tuple. It may be applied to eliminate multiple traversals over the common data structure. The major difficulty in tupling transformation is to find what functions are ..."
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Cited by 38 (20 self)
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Tupling is a wellknown transformation tactic to obtain new efficient recursive functions by grouping some recursive functions into a tuple. It may be applied to eliminate multiple traversals over the common data structure. The major difficulty in tupling transformation is to find what functions are to be tupled and how to transform the tupled function into an efficient one. Previous approaches to tupling transformation are essentially based on fold/unfold transformation. Though general, they suffer from the high cost of keeping track of function calls to avoid infinite unfolding, which prevents them from being used in a compiler. To remedy this situation, we propose a new method to expose recursive structures in recursive definitions and show how this structural information can be explored for calculating out efficient programs by means of tupling. Our new tupling calculation algorithm can eliminate most of multiple data traversals and is easy to be implemented. 1 Introduction Tupli...