Attribute Grammars Fly First-Class How to do Aspect Oriented Programming in Haskell
Artikel i vetenskaplig tidskrift, 2009

Attribute Grammars (AGs), a general-purpose formalism for describing recursive computations over data types, avoid the trade-off which arises when building software incrementally: should it be easy to add new data types and data type alternatives or to add new operations on existing data types? However, AGs are usually implemented as a pre-processor, leaving e. g. type checking to later processing phases and making interactive development, proper error reporting and debugging difficult. Embedding AG into Haskell as a combinator library solves these problems. Previous attempts at embedding AGs as a domain-specific language were based on extensible records and thus exploiting Haskell's type system to check the well-formedness of the AG, but fell short in compactness and the possibility to abstract over oft occurring AG patterns. Other attempts used a very generic mapping for which the AG well-formedness could not be statically checked. We present a typed embedding of AG in Haskell satisfying all these requirements. The key lies in using HList-like typed heterogeneous collections (extensible polymorphic records) and expressing AG well-formedness conditions as type-level predicates (i.e., type-class constraints). By further type-level programming we can also express common programming patterns, corresponding to the typical use cases of monads such as Reader, Writer and State. The paper presents a realistic example of type-class-based type-level programming in Haskell.

Performance

Standardization

HList

Class system

Attribute Grammars

Lazy evaluation

Languages

Design

Haskell

Type-level programming

Författare

M. Viera

Universidad de la Republica

S. D. Swierstra

Universiteit Utrecht

Wouter Swierstra

Chalmers, Data- och informationsteknik, Programvaruteknik (Chalmers)

SIGPLAN Notices (ACM Special Interest Group on Programming Languages)

0362-1340 (ISSN)

Vol. 44 9 245-256

Ämneskategorier

Data- och informationsvetenskap

DOI

10.1145/1596550.1596586

ISBN

9781605583327