Matsuda et al. (Matsuda, K., Hu, Z., Nakano, K., Hamana, M. & Takeichi, M. (2007) Bidirectionalization transformation based on automatic derivation of view complement functions. In Proceedings of the International Conference on Functional Programming. ACM Press, pp. 47–58) and Voigtländer (Voigtländer, J. (2009) Bidirectionalization for free! In Proceedings of Principles of Programming Languages. ACM Press, pp. 165–176) have introduced two techniques that given a source-to-view function provide an update propagation function mapping an original source and an updated view back to an updated source, subject to standard consistency conditions. Previously, we developed a synthesis of the two techniques, based on a separation of shape and content aspects (Voigtländer, J., Hu, Z., Matsuda, K. & Wang, M. (2010) Combining syntactic and semantic bidirectionalization. In Proceedings of the International Conference on Functional Programming. ACM Press, pp. 181–192). Here we carry that idea further, reworking the technique of Voigtländer such that any shape bidirectionalizer (based on the work of Matsuda et al. (2007) or not) can be used as a plug-in, to good effect. We also provide a data-type-generic account, enabling wider reuse, including the use of pluggable bidirectionalization itself as a plug-in.

This paper presents a library for programming with polymorphic dynamic types in the dependently typed programming language Agda. The resulting library allows dynamically typed values with a polymorphic type to be instantiated to a less general (possibly monomorphic) type without compromising type soundness.

This paper describes some experiences of using fractal image compression as the subject of an assignment for a functional programming course using Haskell. The students were fascinated by the reproduction of images from their encodings and engaged well with the exercise which involved only elementary functional programming techniques.

We describe a concise and elegant functional program, written in Haskell, that computes solutions for a classic puzzle known as the “snake cube.” The program reflects some of the fundamental characteristics of the functional style, identifying key abstractions, and defining a small collection of operators for manipulating and working with the associated values. Well-suited for an introductory course on functional programming, this example highlights the use of visualization tools to explain and demonstrate the choices of data structures and algorithms that are used in the development.

The 16th ACM SIGPLAN International Conference on Functional Programming (ICFP) took place on September 19–21, 2011 in Tokyo, Japan. After the conference, the programme committee, chaired by Olivier Danvy, selected several outstanding papers and invited their authors to submit to this special issue of the Journal of Functional Programming. Kenichi Asai and Benjamin C. Pierce acted as editors for these submissions. This issue includes the three accepted articles, each of which provides substantial new material beyond the original conference version. The selected papers represent the importance of various aspects of proof techniques, from theory to practice, all of which aim at verifying realistic programs.

Although type reconstruction for dependently typed languages is common in practical systems, it is still ill-understood. Detailed descriptions of the issues around it are hard to find and formal descriptions together with correctness proofs are non-existing. In this paper, we discuss a one-pass type reconstruction for objects in the logical framework LF, describe formally the type reconstruction process using the framework of contextual modal types, and prove correctness of type reconstruction. Since type reconstruction will find most general types and may leave free variables, we in addition describe abstraction which will return a closed object where all free variables are bound at the outside. We also implemented our algorithms as part of the Beluga language, and the performance of our type reconstruction algorithm is comparable to type reconstruction in existing systems such as the logical framework Twelf.

Many components of a dependently typed programming language are by now well understood, for example, the underlying type theory, type checking, unification and evaluation. How to combine these components into a realistic and usable high-level language is, however, folklore, discovered anew by successive language implementors. In this paper, I describe the implementation of Idris, a new dependently typed functional programming language. Idris is intended to be a general-purpose programming language and as such provides high-level concepts such as implicit syntax, type classes and do notation. I describe the high-level language and the underlying type theory, and present a tactic-based method for elaborating concrete high-level syntax with implicit arguments and type classes into a fully explicit type theory. Furthermore, I show how this method facilitates the implementation of new high-level language constructs.

Correct handling of names and binders is an important issue in meta-programming. This paper presents an embedding of constraint logic programming into the αML functional programming language, which provides a provably correct means of implementing proof search computations over inductive definitions involving names and binders modulo α-equivalence. We show that the execution of proof search in the αML operational semantics is sound and complete with regard to the model-theoretic semantics of formulae, and develop a theory of contextual equivalence for the subclass of αML expressions which correspond to inductive definitions and formulae. In particular, we prove that αML expressions, which denote inductive definitions, are contextually equivalent precisely when those inductive definitions have the same model-theoretic semantics. This paper is a revised and extended version of the conference paper (Lakin, M. R. & Pitts, A. M. (2009) Resolving inductive definitions with binders in higher-order typed functional programming. In Proceedings of the 18th European Symposium on Programming (ESOP 2009), Castagna, G. (ed), Lecture Notes in Computer Science, vol. 5502. Berlin, Germany: Springer-Verlag, pp. 47–61) and draws on material from the first author's PhD thesis (Lakin, M. R. (2010) An Executable Meta-Language for Inductive Definitions with Binders. University of Cambridge, UK).

Most interactive theorem provers provide support for some form of user-customizable proof automation. In a number of popular systems, such as Coq and Isabelle, this automation is achieved primarily through tactics, which are programmed in a separate language from that of the prover's base logic. While tactics are clearly useful in practice, they can be difficult to maintain and compose because, unlike lemmas, their behavior cannot be specified within the expressive type system of the prover itself.

We propose a novel approach to proof automation in Coq that allows the user to specify the behavior of custom automated routines in terms of Coq's own type system. Our approach involves a sophisticated application of Coq's canonical structures, which generalize Haskell type classes and facilitate a flexible style of dependently-typed logic programming. Specifically, just as Haskell type classes are used to infer the canonical implementation of an overloaded term at a given type, canonical structures can be used to infer the canonical proof of an overloaded lemma for a given instantiation of its parameters. We present a series of design patterns for canonical structure programming that enable one to carefully and predictably coax Coq's type inference engine into triggering the execution of user-supplied algorithms during unification, and we illustrate these patterns through several realistic examples drawn from Hoare Type Theory. We assume no prior knowledge of Coq and describe the relevant aspects of Coq type inference from first principles.

A metamorphism is an unfold after a fold, consuming an input by the fold then generating an output by the unfold. It is typically useful for converting data representations, e.g., radix conversion of numbers. (Bird and Gibbons, Lecture Notes in Computer Science, vol. 2638, 2003, pp. 1–26) have shown that metamorphisms can be incrementally processed in streaming style when a certain condition holds because part of the output can be determined before the whole input is given. However, whereas radix conversion of fractions is amenable to streaming, radix conversion of natural numbers cannot satisfy the condition because it is impossible to determine part of the output before the whole input is completed. In this paper, we present a jigsaw model in which metamorphisms can be partially processed for outputs even when the streaming condition does not hold. We start with how to describe the 3-to-2 radix conversion of natural numbers using our model. The jigsaw model allows us to process metamorphisms in a flexible way that includes parallel computation. We also apply our model to other examples of metamorphisms.

This paper presents a formal definition and machine-checked soundness proof for a very expressive type-and-capability system, that is, a low-level type system that keeps precise track of ownership and side effects. The programming language has first-class functions and references. The type system's features include the following: universal, existential, and recursive types; subtyping; a distinction between affine and unrestricted data; support for strong updates; support for naming values and heap fragments via singleton and group regions; a distinction between ordinary values (which exist at runtime) and capabilities (which do not); support for dynamic reorganizations of the ownership hierarchy by disassembling and reassembling capabilities; and support for temporarily or permanently hiding a capability via frame and anti-frame rules. One contribution of the paper is the definition of the type-and-capability system itself. We present the system as modularly as possible. In particular, at the core of the system, the treatment of affinity, in the style of dual intuitionistic linear logic, is formulated in terms of an arbitrary monotonic separation algebra, a novel axiomatization of resources, ownership, and the manner in which they evolve with time. Only the peripheral layers of the system are aware that we are dealing with a specific monotonic separation algebra, whose resources are references and regions. This semi-abstract organization should facilitate further extensions of the system with new forms of resources. The other main contribution is a machine-checked proof of type soundness. The proof is carried out in the Wright and Felleisen's syntactic style. This offers an evidence that this relatively simple-minded proof technique can scale up to systems of this complexity, and constitutes a viable alternative to more sophisticated semantic proof techniques. We do not claim that the syntactic technique is superior: We simply illustrate how it is used and highlight its strengths and shortcomings.

This paper presents a semantics of self-adjusting computation and proves that the semantics is correct and consistent. The semantics introduces memoizing change propagation, which enhances change propagation with the classic idea of memoization to enable reuse of computations even when memory is mutated via side effects. During evaluation, computation reuse via memoization triggers a change-propagation algorithm that adapts the reused computation to the memory mutations (side effects) that took place since the creation of the computation. Since the semantics includes both memoization and change propagation, it involves both non-determinism (due to memoization) and mutation (due to change propagation). Our consistency theorem states that the non-determinism is not harmful: any two evaluations of the same program starting at the same state yield the same result. Our correctness theorem states that mutation is not harmful: Self-adjusting programs are compatible with purely functional programming. We formalize the semantics and its meta-theory in the LF logical framework and machine check our proofs using Twelf.

Refactoring is the process of changing the design of a program without changing what it does. Typical refactorings, such as function extraction and generalisation, are intended to make a program more amenable to extension, more comprehensible and so on. Refactorings differ from other sorts of program transformation in being applied to source code, rather than to a ‘core’ language within a compiler, and also in having an effect across a code base, rather than to a single function definition, say. Because of this, there is a need to give automated support to the process. This paper reflects on our experience of building tools to refactor functional programs written in Haskell (HaRe) and Erlang (Wrangler). We begin by discussing what refactoring means for functional programming languages, first in theory, and then in the context of a larger example. Next, we address system design and details of system implementation as well as contrasting the style of refactoring and tooling for Haskell and Erlang. Building both tools led to reflections about what particular refactorings mean, as well as requiring analyses of various kinds, and we discuss both of these. We also discuss various extensions to the core tools, including integrating the tools with test frameworks; facilities for detecting and eliminating code clones; and facilities to make the systems extensible by users. We then reflect on our work by drawing some general conclusions, some of which apply particularly to functional languages, while many others are of general value.

This pearl is devoted to a problem posed by Don Knuth about how to justify a certain array-based algorithm for changing the way an undirected graph is represented. In order to set the scene, we delay describing the precise problem until Section 4. Knuth (2011) recorded three different solutions, though no proofs of correctness were provided, nor even much explanation of why they worked. Recently, he asked various computer scientists interested in formal program development whether any of the proposed solutions “could have been discovered in a disciplined manner.” In what follows we respond by developing a purely functional solution. The solution makes heavy use of the operations in the Haskell library Data.Array, and the whole exercise turns out to be a fascinating study of the arithmetic of graphs and arrays. One of the conditions of the problem is that the final algorithm has to be in situ, but we will get to that in due course.

Commercial Users of Functional Programming (CUFP) is an annual workshop that is aimed at the community of software developers who use functional programming in real-world settings. This scribe report covers the talks that were delivered at the 2012 workshop, which was held in association with International Conference on Functional Programming (ICFP) in Copenhagen, Denmark. The goal of the report is to give the reader a sense of what went on, rather than to reproduce the full details of the talks. Videos and slides from all the talks are available online at http://cufp.org.

Lambda calculus is the basis of functional programming and higher order proof assistants. However, little is known about combinatorial properties of lambda terms, in particular, about their asymptotic distribution and random generation. This paper tries to answer questions like: How many terms of a given size are there? What is a ‘typical’ structure of a simply typable term? Despite their ostensible simplicity, these questions still remain unanswered, whereas solutions to such problems are essential for testing compilers and optimizing programs whose expected efficiency depends on the size of terms. Our approach toward the aforementioned problems may be later extended to any language with bound variables, i.e., with scopes and declarations. This paper presents two complementary approaches: one, theoretical, uses complex analysis and generating functions, the other, experimental, is based on a generator of lambda terms. Thanks to de Bruijn indices (de Bruijn, N. (1972) Lambda calculus notation with nameless dummies, a tool for automatic formula manipulation, with application to the Church-Rosser theorem. Indagat. Math.34(5), 381–392), we provide three families of formulas for the number of closed lambda terms of a given size and we give four relations between these numbers which have interesting combinatorial interpretations. As a by-product of the counting formulas, we design an algorithm for generating λ-terms. Performed tests provide us with experimental data, like the average depth of bound variables and the average number of head lambdas. We also create random generators for various sorts of terms. Thereafter, we conduct experiments that answer questions like: What is the ratio of simply typable terms among all terms? (Very small!) How are simply typable lambda terms distributed among all lambda terms? (A typable term almost always starts with an abstraction.) In this paper, abstractions and applications have size 1 and variables have size 0.

Distributed applications are difficult to program reliably and securely. Dependently typed functional languages promise to prevent broad classes of errors and vulnerabilities, and to enable program verification to proceed side-by-side with development. However, as recursion, effects, and rich libraries are added, using types to reason about programs, specifications, and proofs becomes challenging. We present F*, a full-fledged design and implementation of a new dependently typed language for secure distributed programming. Our language provides arbitrary recursion while maintaining a logically consistent core; it enables modular reasoning about state and other effects using affine types; and it supports proofs of refinement properties using a mixture of cryptographic evidence and logical proof terms. The key mechanism is a new kind system that tracks several sub-languages within F* and controls their interaction. F* subsumes two previous languages, F7 and Fine. We prove type soundness (with proofs mechanized in Coq) and logical consistency for F*. We have implemented a compiler that translates F* to .NET bytecode, based on a prototype for Fine. F* provides access to libraries for concurrency, networking, cryptography, and interoperability with C#, F#, and the other .NET languages. The compiler produces verifiable binaries with 60% code size overhead for proofs and types, as much as a 45x improvement over the Fine compiler, while still enabling efficient bytecode verification. We have programmed and verified nearly 50,000 lines of F* including new schemes for multi-party sessions; a zero-knowledge privacy-preserving payment protocol; a provenance-aware curated database; a suite of web-browser extensions verified for authorization properties; a cloud-hosted multi-tier web application with a verified reference monitor; the core F* typechecker itself; and programs translated to F* from other languages such as F7 and JavaScript.