We introduce the arrow calculus, a metalanguage for manipulating Hughes’s arrows with close relations both to Moggi’s metalanguage for monads and to Paterson’s arrow notation. Arrows are classically defined by extending lambda calculus with three constructs satisfying nine (somewhat idiosyncratic) laws; in contrast, the arrow calculus adds four constructs satisfying five laws (which fit two well-known patterns). The five laws were previously known to be sound; we show that they are also complete, and hence that the five laws may replace the nine. 1

monads are promiscuous

A permutation phrase is a sequence of elements (possibly of different types) in which each element occurs exactly once and the order is irrelevant. Some of the permutable elements may be optional. We show a way to extend a parser combinator library with support for parsing such free-order constructs. A user of the library can easily write parsers for permutation phrases and does not need to care about checking and reordering the recognised elements. Possible applications include the generation of parsers for attributes of XML tags and Haskell's record syntax.

A domain-specific embedded language (DSEL) is a domain-specific programming language with no concrete syntax of its own. Defined as a set of combinators encapsulated in a module, it borrows the syntax and tools (such as type-checkers and compilers) of its host language; hence it is economical to design, introduce, and maintain. Unfortunately, this economy is counterbalanced by a lack of room for growth. DSELs cannot match sophisticated domain-specific languages that offer tools for domainspecific error-checking and optimisation. These tools are usually based on syntactic analyses, so they do not work on DSELs. Abstract interpretation is a technique ideally suited to the analysis of DSELs, due to its semantic, rather than syntactic, approach. It is based upon the observation that analysing a program is equivalent to evaluating it over an abstract semantic domain. The mathematical properties of the abstract domain are such that evaluation reduces to solving a mutually recursive set of equations. This thesis shows how abstract interpretation can be applied to a DSEL by replacing it with an abstract implementation

Abstract. This paper is an exploration in a functional programming framework of isomorphisms between elementary data types (natural numbers, sets, multisets, finite functions, permutations binary decision diagrams, graphs, hypergraphs, parenthesis languages, dyadic rationals, primes, DNA sequences etc.) and their extension to hereditarily finite universes through hylomorphisms derived from ranking/unranking and pairing/unpairing operations. An embedded higher order combinator language provides any-to-any encodings automatically. Besides applications to experimental mathematics, a few examples of “free algorithms ” obtained by transferring operations between data types are shown. Other applications range from stream iterators on combinatorial objects to self-delimiting codes, succinct data representations and generation of random instances. The paper covers 60 data types and, through the use of the embedded combinator language, provides 3660 distinct bijective transformations between them. The self-contained source code of the paper, as generated from a literate Haskell program, is available at

We investigate what the correct categorical formulation of Hughes ’ Arrows should be. It has long been folklore that Arrows, a functional programming construct, and Freyd categories, a categorical notion due to Power, Robinson and Thielecke, are somehow equivalent. In this paper, we show that the situation is more subtle. By considering Arrows wholly within the base category we derive two alternative formulations of Freyd category that are equivalent to Arrows—enriched Freyd categories and indexed Freyd categories. By imposing a further condition, we characterise those indexed Freyd categories that are isomorphic to Freyd categories. The key differentiating point is the number of inputs available to a computation and the structure available on them, where structured input is modelled using comonads. 1

There are numerous ways to implement a parser for a given syntax; using parser combinators is a powerful approach to parsing which derives much of its power and expressiveness from the type system and semantics of the host programming language. This tutorial begins with the construction of a small library of parsing combinators. This library introduces the basics of combinator parsing and, more generally, demonstrates how domain specific embedded languages are able to leverage the facilities of the host language. After having constructed our small combinator library, we investigate some shortcomings of the naïve implementation introduced in the first part, and incrementally develop an implementation without these problems. Finally we discuss some further extensions of the presented library and compare our approach with similar libraries. 1