With this issue of the Journal of Functional Programming, we transition to a new leadership. Xavier Leroy, who has faithfully served as co-Editor in Chief since 2007, is stepping down. After a short apprenticeship over the past year, Benjamin Pierce is taking his place.

Since Findler and Felleisen (Findler, R. B. & Felleisen, M. 2002) introduced higher-order contracts, many variants have been proposed. Broadly, these fall into two groups: some follow Findler and Felleisen (2002) in using latent contracts, purely dynamic checks that are transparent to the type system; others use manifest contracts, where refinement types record the most recent check that has been applied to each value. These two approaches are commonly assumed to be equivalent—different ways of implementing the same idea, one retaining a simple type system, and the other providing more static information. Our goal is to formalize and clarify this folklore understanding. Our work extends that of Gronski and Flanagan (Gronski, J. & Flanagan, C. 2007), who defined a latent calculus λC and a manifest calculus λH, gave a translation φ from λC to λH, and proved that if a λC term reduces to a constant, so does its φ-image. We enrich their account with a translation ψ from λH to λC and prove an analogous theorem. We then generalize the whole framework to dependent contracts, whose predicates can mention free variables. This extension is both pragmatically crucial, supporting a much more interesting range of contracts, and theoretically challenging. We define dependent versions of λH and two dialects (“lax” and “picky”) of λC, establish type soundness—a substantial result in itself, for λH — and extend φ and ψ accordingly. Surprisingly, the intuition that the latent and manifest systems are equivalent now breaks down: the extended translations preserve behavior in one direction, but in the other, sometimes yield terms that blame more.

Functional languages are suitable for transformational developments of programs. However, accumulative functions, or in particular tail-recursive functions, are known to be less suitable for manipulation. In this paper, we propose a program transformation named “IO swapping” that swaps call-time and return-time computations. It moves computations in accumulative parameters to results and thereby enables interesting transformations. We demonstrate effectiveness of IO swapping by several applications: deforestation, higher order removal, program inversion, and manipulation of circular programs.

We introduce the notion of discrimination as a generalization of both sorting and partitioning, and show that discriminators (discrimination functions) can be defined generically, by structural recursion on representations of ordering and equivalence relations. Discriminators improve the asymptotic performance of generic comparison-based sorting and partitioning, and can be implemented not to expose more information than the underlying ordering, respectively equivalence relation. For a large class of order and equivalence representations, including all standard orders for regular recursive first-order types, the discriminators execute in the worst-case linear time. The generic discriminators can be coded compactly using list comprehensions, with order and equivalence representations specified using Generalized Algebraic Data Types. We give some examples of the uses of discriminators, including the most-significant digit lexicographic sorting, type isomorphism with an associative-commutative operator, and database joins. Source code of discriminators and their applications in Haskell is included. We argue that built-in primitive types, notably pointers (references), should come with efficient discriminators, not just equality tests, since they facilitate the construction of discriminators for abstract types that are both highly efficient and representation-independent.

My main reason for wanting to read this book was to find out what a well-known publicist from the world of OO would have to say about the state of the art of domain specific languages (DSLs), in particular when it comes to type error feedback, functional programming, and the combination. As most readers will be aware, languages like Scheme and Haskell are very well suited to embed DSLs in: Scheme can be considered a core language to which new language facilities can be easily added by means of hygienic syntax macro's (Abelson et al. 1998), and there are so many papers on embedded DSLs in Haskell (Hudak, 1998), that any realistic selection would aggravate more people than I would please. Great was my disappointment when I read on page XXV that these topics were not discussed at all in the book. Although I can imagine that Fowler does not feel comfortable writing about subjects he is not sufficiently at home with, the question does arise whether the title of this book is sufficiently covered by its contents.