2005ACM SIGPLAN NoticesRequires access

Essential language support for generic programming

Jeremy G. Siek, Andrew Lumsdaine

Open publisher page 50 citations

Abstract

Concepts are an essential language feature for generic programming in the large. Concepts allow for succinct expression of constraints on type parameters of generic algorithms, enable systematic organization of problem domain abstractions, and make generic algorithms easier to use. In this paper we present the design of a type system and semantics for concepts that is suitable for non-type-inferencing languages. Our design shares much in common with the type classes of Haskell, though our primary influence is from best practices in the C++ community, where concepts are used to document type requirements for templates in generic libraries. Concepts include a novel combination of associated types and same-type constraints that do not appear in type classes, but that are similar to nested types and type sharing in ML.

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What this paper is about

Concepts are an essential language feature for generic programming in the large. Concepts allow for succinct expression of constraints on type parameters of generic algorithms, enable systematic organization of problem domain abstractions, and make generic algorithms easier to use. In this paper we present the design of a type system and semantics for concepts that is suitable for non-type-inferencing languages. Our design shares much in common with the type classes of Haskell, though our primary influence is from best practices in the C++ community, where concepts are used to document type requirements for templates in generic libraries. Concepts include a novel combination of associated types and same-type constraints that do not appear in type classes, but that are similar to nested types and type sharing in ML.

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Available abstract

Concepts are an essential language feature for generic programming in the large. Concepts allow for succinct expression of constraints on type parameters of generic algorithms, enable systematic organization of problem domain abstractions, and make generic algorithms easier to use. In this paper we present the design of a type system and semantics for concepts that is suitable for non-type-inferencing languages. Our design shares much in common with the type classes of Haskell, though our primary influence is from best practices in the C++ community, where concepts are used to document type requirements for templates in generic libraries. Concepts include a novel combination of associated types and same-type constraints that do not appear in type classes, but that are similar to nested types and type sharing in ML.

Key concepts: Computer science, Haskell, Programming language, Generic programming, Type (biology), Template, Domain-specific language, Functional programming

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