Type inference for generic Haskell

2007

The last decade has seen a number of approaches to datatype-generic programming: PolyP, Functorial ML,'Scrap Your Boilerplate', Generic Haskell,'Generics for the Masses', and so on. The approaches vary in sophistication and target audience: some propose full-blown programming languages, some suggest libraries, some can be seen as categorical programming methods. In these lecture notes we compare the various approaches to datatype-generic programming in Haskell.

2003

Generic Haskell is an extension of Haskell that supports the construction of generic programs. These lecture notes discuss three advanced generic programming applications: generic dictionaries, compressing XML documents, and the zipper: a data structure used to represent a tree together with a subtree that is the focus of attention, where that focus may move left, right, up or down the tree.

2009

These lecture notes introduce libraries for datatype-generic programming in Haskell. We introduce three characteristic generic programming libraries: lightweight implementation of generics and dynamics, extensible and modular generics for the masses, and scrap your boilerplate. We show how to use them to use and write generic programs. In the case studies for the different libraries we introduce generic components of a medium-sized application which assists a student in solving mathematical exercises.

2011

Abstract Generic Haskell is an extension of Haskell that supports datatype generic programming. The central idea of Generic Haskell is to interpret a type by a function, the so-called instance of a generic function at that type. Since types in Haskell include parametric types such as' list of', Generic Haskell represents types by terms of the simply-typed lambda calculus.

2012

In Haskell, there is a clear distinction between values, types, and kinds. Values are built with constructors, such as True, which we colour in blue; we do not colour numerals, characters, or strings: Just 3, (Right 'p' Left "abc"). Datatypes, type synonyms, type variables, indexed families, and type classes are coloured in orange: Bool, Show α ⇒ Show [ α ], type family PF α. Kinds and kind variables are coloured in green: , → , Constraint. For simplicity we do not colour the arrow operator, as it can appear at different levels. Agda code The distinction between values and types is less clear in Agda. Our convention is to use blue for constructors (e.g. refl), orange for identifiers of type Set (e.g. _≡_), and green for identifiers of type Set 1 or (for simplicity) higher (e.g. Set). 2.2.3 Isomorphisms We have mentioned that some types are equivalent to others without formally defining this equivalence. When we say two types are equivalent we mean that they are isomorphic. The concept of isomorphism can be succinctly summarised as an Agda record type:

ACM SIGPLAN …, 2009

Datatype-generic programming is defining functions that depend on the structure, or "shape", of datatypes. It has been around for more than 10 years, and a lot of progress has been made, in particular in the lazy functional programming language Haskell. There are more than 10 proposals for generic programming libraries or language extensions for Haskell. To compare and characterize the many generic programming libraries in a typed functional language, we introduce a set of criteria and develop a generic programming benchmark: a set of characteristic examples testing various facets of datatype-generic programming. We have implemented the benchmark for nine existing Haskell generic programming libraries and present the evaluation of the libraries. The comparison is useful for reaching a common standard for generic programming, but also for a programmer who has to choose a particular approach for datatype-generic programming.

2000

Abstract 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.

2007

We report on an extension of Haskell with type(-level) functions and equality constraints. We illustrate their usefulness in the context of phantom types, GADTs and type classes. Problems in the context of type checking are identified and we sketch our solution: a decidable type checking algorithm for a restricted class of type functions. Moreover, functional dependencies are now obsolete: we show how they can be encoded as type functions.

Generic Programming, 2003

2006

Abstract A generic function is a function that is defined on the structure of data types: with a single definition, we obtain a function that works for many data types. In contrast, an ad-hoc polymorphic function requires a separate implementation for each data type. Previous work by Hinze on lightweight generic programming has introduced techniques that allow the definition of generic functions directly in Haskell.

Sigplan Notices, 2010

Haskell's deriving mechanism supports the automatic generation of instances for a number of functions. The Haskell 98 Report only specifies how to generate instances for the Eq, Ord, Enum, Bounded, Show, and Read classes. The description of how to generate instances is largely informal. The generation of instances imposes restrictions on the shape of datatypes, depending on the particular class to derive. As a consequence, the portability of instances across different compilers is not guaranteed.