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A polytypic value is one that is defined by induction on the structure of types. In Haskell the type structure is described by the so-called kind system, which distinguishes between manifest types like the type of integers and functions on types like the list type constructor. Previous approaches to polytypic programming were restricted in that they only allowed to parameterize values by types of one fixed kind. In this paper we show how to define values that are indexed by types of arbitrary kinds. It appears that these polytypic values possess types that are indexed by kinds. We present several examples that demonstrate that the additional exibility is useful in practice. One paradigmatic example is the mapping function, which describes the functorial action on arrows. A single polytypic definition yields mapping functions for datatypes of arbitrary kinds including first- and higher-order functors. Polytypic values enjoy polytypic properties. Using kind-indexed logical relations we prove...

PolyP extends a functional language (a subset of Haskell) with a construct for defining polytypic functions by induction on the structure of user-defined 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.

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Generic Haskell is an extension of Haskell that supports the construction of generic programs. During the development of several applications, such as an XML editor and compressor, we encountered a number of limitations with the existing (Classic) Generic Haskell language, as implemented by the current Generic Haskell compiler. Specifically,

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.

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 user-dened type classes and for classes that abstract over type constructors of rst-order 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...

Run-time type analysis is an increasingly important linguistic mechanism in modern programming languages. Language runtime systems use it to implement services such as accurate garbage collection, serialization, cloning and structural equality. Component frameworks rely on it to provide reflection mechanisms so they may discover and interact with program interfaces dynamically. Run-time type analysis is also crucial for large, distributed systems that must be dynamically extended, because it allows those systems to check program invariants when new code and new forms of data are added. Finally, many generic user-level algorithms for iteration, pattern matching, and unification can be defined through type analysis mechanisms. However, existing frameworks for run-time type analysis were designed for simple type systems. They do not scale well to the sophisticated type systems of modern and next-generation programming languages that include complex constructs such as first-class abstract types, recursive types, objects, and type parameterization. In addition, facilities to support type analysis often require complicated

This paper describes structural polymorphism, a new form of type polymorphism appropriate to functional languages featuring user-defined algebraic data types (e.g., Standard ML, Haskell and Miranda 1 ). The approach extends the familiar notion of parametric polymorphism by allowing the definition of functions which are generic with respect to data structures as well as to individual types. For example, structural polymorphism accommodates generalizations of the usual length and map functions which may be applied not only to lists, but also to trees, binary trees or similar algebraic structures. Under traditional polymorphic type systems, these functions may be defined for arbitrary component types, but must be (laboriously) re-defined for every distinct data structure. In this sense, our approach also extends the spirit of parametric polymorphism, in that it provides the programmer relief from the burden of unnecessary repetitive effort. The mechanism we will use to realize this form of polymorphism is inspired by a feature familiar to functional programmers, namely the pattern abstraction. Pattern abstractions generalize the usual lambda abstraction (x.e) in that they are comprised of multiple pattern/expression clauses, rather than just a single bound-variable/expression pair. By analogy with pattern abstractions, we generalize polymorphic type abstractions (Òå.e) to type-pattern abstractions, which are comprised of multiple type-pattern/expression pairs. The types given to type-pattern abstractions are universally quantified, just as for traditional type abstractions, but the universal quantifiers are now justified by a recursive analysis of the forms of all possible type instantiations, rather than by parametric independence with respect to a type variable. (x:+.e) ...

Type-directed programming is an important and widely used paradigm in the design of software. With this form of programming, a program may analyze type information to determine its behavior. By analyzing the structure of data, many operations, such as serialization, cloning, structural equality, and iterators, may be defined once, for all types of data. The benefit of type-directed programming is that as software evolves, operations need not be updated---they will automatically adapt to new data forms. Otherwise, each of these operations must be individually redefined for each type of data, forcing programmers to revisit the same program logic many times during a program's lifetime.