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,

Abstract. Generic Haskell is an extension of Haskell that supports the construction of generic programs. These lecture notes describe the basic constructs of Generic Haskell and highlight the underlying theory. Generic programming aims at making programming more effective by making it more general. Generic programs often embody non-traditional kinds of polymorphism. Generic Haskell is an extension of Haskell [38] that supports the construction of generic programs. Generic Haskell adds to Haskell the notion of structural polymorphism, the ability to define a function (or a type) by induction on the structure of types. Such a function is generic in the sense that it works not only for a specific type but for a whole class of types. Typical examples include equality, parsing and pretty printing, serialising, ordering, hashing, and so on. The lecture notes on Generic Haskell are organized into two parts. This first part motivates the need for genericity, describes the basic constructs of Generic Haskell, puts Generic Haskell into perspective, and highlights the underlying theory. The second part entitled “Generic Haskell: applications ” delves deeper into the language discussing three non-trivial applications of Generic Haskell: generic dictionaries, compressing XML documents, and a generic version of the zipper data type. The first part is organized as follows. Section 1 provides some background discussing type systems in general and the type system of Haskell in particular. Furthermore, it motivates the basic constructs of Generic Haskell. Section 2 takes a closer look at generic definitions and shows how to define some popular generic functions. Section 3 highlights the theory underlying Generic Haskell and discusses its implementation. Section 4 concludes. 1

Writing boilerplate code is a royal pain. Generic programming promises to alleviate this pain by allowing the programmer to write a generic "recipe" for boilerplate code, and use that recipe in many places. In earlier work we introduced the "Scrap your boilerplate " approach to generic programming, which cunningly exploits Haskell's existing type-class mechanism to support generic transformations and queries.

We show how to write generic programs and proofs in MartinL of type theory. To this end we consider several extensions of MartinL of's logical framework for dependent types. Each extension has a universes of codes (signatures) for inductively defined sets with generic formation, introduction, elimination, and equality rules. These extensions are modeled on Dybjer and Setzer's finitely axiomatized theories of inductive-recursive definitions, which also have a universe of codes for sets, and generic formation, introduction, elimination, and equality rules.

We give two nite axiomatizations of indexed inductive-recursive de nitions in intuitionistic type theory. They extend our previous nite axiomatizations of inductive-recursive de nitions of sets to indexed families of sets and encompass virtually all de nitions of sets which have been used in intuitionistic type theory. The more restricted of the two axiomatization arises naturally by considering indexed inductive-recursive de nitions as initial algebras in slice categories, whereas the other admits a more general and convenient form of an introduction rule.

Abstract. We introduce the notion of containers as a mathematical formalisation of the idea that many important datatypes consist of templates where data is stored. We show that containers have good closure properties under a variety of constructions including the formation of initial algebras and final coalgebras. We also show that containers include strictly positive types and shapely types but that there are containers which do not correspond to either of these. Further, we derive a representation result classifying the nature of polymorphic functions between containers. We finish this paper with an application to the theory of shapely types and refer to a forthcoming paper which applies this theory to differentiable types. 1

Abstract. A generic function is defined by induction on the structure of types. The structure of a data type can be defined in several ways. For example, in PolyP a pattern functor gives the structure of a data type viewed as a fixed point, and in Generic Haskell a structural representation type gives an isomorphic type view of a data type in terms of sums of products. Depending on this generic view on the structure of data types, some generic functions are easier, more difficult, or even impossible to define. Furthermore, the efficiency of some generic functions can be improved by choosing a different view. This paper introduces generic views on data types and shows why they are useful. Furthermore, it shows how generic views have been added to Generic Haskell, an extension of the functional programming language Haskell that supports the construction of generic functions. The separation between inductive definitions on type structure and generic views allows us to combine many approaches to generic programming in a single framework. 1

We construct a logical framework supporting datatypes that mix binding and computation, implemented as a universe in the dependently typed programming language Agda 2. We represent binding pronominally, using well-scoped de Bruijn indices, so that types can be used to reason about the scoping of variables. We equip our universe with datatype-generic implementations of weakening, substitution, exchange, contraction, and subordination-based strengthening, so that programmers need not reimplement these operations for each individual language they define. In our mixed, pronominal setting, weakening and substitution hold only under some conditions on types, but we show that these conditions can be discharged automatically in many cases. Finally, we program a variety of standard difficult test cases from the literature, such as normalization-by-evaluation for the untyped λ-calculus, demonstrating that we can express detailed invariants about variable usage in a program’s type while still writing clean and clear code.

Abstract. In this paper we use the Epigram language to define the universe of regular tree types—closed under empty, unit, sum, product and least fixpoint. We then present a generic decision procedure for Epigram’s in-built equality at each type, taking a complementary approach to that of Benke, Dybjer and Jansson [7]. We also give a generic definition of map, taking our inspiration from Jansson and Jeuring [21]. Finally, we equip the regular universe with the partial derivative which can be interpreted functionally as Huet’s notion of ‘zipper’, as suggested by McBride in [27] and implemented (without the fixpoint case) in Generic Haskell by Hinze, Jeuring and Löh [18]. We aim to show through these examples that generic programming can be ordinary programming in a dependently typed language. 1

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