The Zip Calculus

Tullsen, Mark

doi:10.1007/10722010_3

Cited by 3 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Tullsen [15] attempts to bring non-uniform variable-arity functions to Haskell via the Zip Calculus, a type system with restricted dependent types and special kinds that serve as tuple dimensions. This work is theoretical and comes without practical evaluation.…”

Section: Related Workmentioning

confidence: 99%

Practical Variable-Arity Polymorphism

Strickland

Tobin-Hochstadt

Felleisen

2009

Programming Languages and Systems

View full text Add to dashboard Cite

Abstract. Just as some functions have uniform behavior over distinct types, other functions have uniform behavior over distinct arities. These variable-arity functions are widely used in scripting languages such as Scheme and Python. Statically typed languages also accommodate modest forms of variable-arity functions, but even ML and Haskell, languages with highly expressive type systems, cannot type check the wide variety of variable-arity functions found in untyped functional languages. Consequently, their standard libraries contain numerous copies of the same function definition with slightly different names. As part of the Typed Scheme project-an on-going effort to create an explicitly typed sister language for PLT Scheme-we have designed and implemented an expressive type system for variable-arity functions. Our practical validation in the context of our extensive code base confirms the usefulness of the enriched type system.

show abstract

Section: Related Workmentioning

confidence: 99%

Practical Variable-Arity Polymorphism

Strickland

Tobin-Hochstadt

Felleisen

2009

Programming Languages and Systems

View full text Add to dashboard Cite

show abstract

“…To some extent, our work represents not just an implementation of generic programming, but a formally checked presentation of its theory. We chose the concrete datatypes of Haskell as our example, delivering power comparable to that of Generic Haskell [7], but we could equally have chosen Tullsen 's calculus of polyadic functions [28] or Pierce and Hosoya's language of generic operations for valid XML [13]. With dependently types, generic programming is just programming: it is not necessary to write a new compiler each time a useful universe presents itself.…”

Section: Conclusion and Further Workmentioning

confidence: 99%

Generic Programming within Dependently Typed Programming

Altenkirch

McBride

2003

Generic Programming

View full text Add to dashboard Cite

We show how higher kinded generic programming can be represented faithfully within a dependently typed programming system. This development has been implemented using the OLEG system. The present work can be seen as evidence for our thesis that extensions of type systems can be done by programming within a dependently typed language, using data as codes for types. IntroductionGeneric programming [4,12,14,15]

show abstract

“…Many kinds of genericity can be programmed directly by identifying a datatype code for the domain of types being addressed. Given a suitable type-level language, much-needed extensions such as Tullsen's "Zip Calculus" (Tullsen, 2000) and the "polytypic" programming of Jansson, Jeuring, Hinze et al (Jansson & Jeuring, 1997;Hinze & Jeuring, 2001) could be implemented as libraries for Haskell, rather than compiler extensions.…”

Section: What Can Be Done?mentioning

confidence: 99%

Faking it Simulating dependent types in Haskell

McBride

2002

J. Funct. Prog.

View full text Add to dashboard Cite

Dependent types reflect the fact that validity of data is often a relative notion by allowing prior data to affect the types of subsequent data. Not only does this make for a precise type system, but also a highly generic one: both the type and the program for each instance of a family of operations can be computed from the data which codes for that instance. Recent experimental extensions to the Haskell type class mechanism give us strong tools to relativize types to other types. We may simulate some aspects of dependent typing by making counterfeit type-level copies of data, with type constructors simulating data constructors and type classes simulating datatypes. This paper gives examples of the technique and discusses its potential.

show abstract

The Zip Calculus

Cited by 3 publications

References 9 publications

Practical Variable-Arity Polymorphism

Practical Variable-Arity Polymorphism

Generic Programming within Dependently Typed Programming

Faking it Simulating dependent types in Haskell

Contact Info

Product

Resources

About