Nested datatypes are families of datatypes that are indexed over all types such that the constructors may relate different family members (unlike the homogeneous lists). Moreover, the argument types of the constructors refer to indices given by expressions in which the family name may occur. Especially in this case of true nesting, termination of functions that traverse these data structures is far from being obvious. A joint paper with A. Abel and T. Uustalu (Theor. Comput. Sci., 333 (1–2), 2005, pp. 3–66) proposed iteration schemes that guarantee termination not by structural requirements but just by polymorphic typing. They are generic in the sense that no specific syntactic form of the underlying datatype “functor” is required. However, there was no induction principle for the verification of the programs thus obtained, although they are well known in the usual model of initial algebras on endofunctor categories. The new contribution is a representation of nested datatypes in intensional type theory (more specifically, in the calculus of inductive constructions) that is still generic and covers true nesting, guarantees termination of all expressible programs, and has an induction principle that allows to prove functoriality of monotonicity witnesses (maps for nested datatypes) and naturality properties of iteratively defined polymorphic functions.

The construction of a parallel vision system from Standard ML prototypes is presented. The system recognises 3D objects from 2D scenes through edge detection, grouping of edges into straight lines and line junction based model matching. Functional prototyping for parallelism is illustrated through the development of the straight line detection component. The assemblage of the whole system from prototyped components is then considered and its performance discussed.

The presence of side effects in even a very simple language of expressions gives rise to a number of semantic questions. The issue of evaluation order becomes a crucial one and, unless a specific order is enforced, the language becomes non-deterministic. In this paper we study the denotational semantics of such a language under a variety of possible evaluation strategies, from simpler to more complex, concluding with unspecified evaluation order, unspecified order of side effects and the mechanism of sequence points that is particular to the ANSI C programming language. In doing so, we adopt a dialect of Haskell as a metalanguage, instead of mathematical notation, and use monads and monad transformers to improve modularity. In this way, only small modifications are required for each transition. The result is a better understanding of different evaluation strategies and a unified way of specifying their semantics. Furthermore, a significant step is achieved towards a complete and accurate semantics for ANSI C.

Term-rewriting systems can be expressed as generic programs parameterised over the shape of the terms being rewritten. Previous implementations of generic rewriting libraries require users to either adapt the datatypes that are used to describe these terms or to specify rewrite rules as functions. These are fundamental limitations: the former implies a lot of work for the user, while the latter makes it hard if not impossible to document, test, and analyze rewrite rules. In this article, we demonstrate how to overcome these limitations by making essential use of type-indexed datatypes. Our approach is lightweight in that it is entirely expressible in Haskell with GADTs and type families and can be readily packaged for use with contemporary Haskell distributions.

Macros still haven't made their way into typed higher-order programming languages such as Haskell and Standard ML. Therefore, to extend the expressiveness of Haskell or Standard ML, one must express new linguistic features in terms of functions that fit within the static type systems of these languages. This is particularly challenging when introducing features that span across multiple types and that bind variables. We address this challenge by developing, in a step by step manner, mechanisms for encoding patterns and pattern matching in Haskell in a type-safe way.

Sheet-defined functions (SDFs) bring modularity and abstraction to the world of spreadsheets. Alas, end users naturally write SDFs that work over fixed-size arrays, which limits their reusability. To help end user programmers write more reusable SDFs, we describe a principled approach to generalising such functions to become elastic SDFs that work over inputs of arbitrary size. We prove that under natural, checkable conditions, our algorithm returns the principal generalisation of an input SDF. We describe a formal semantics and several efficient implementation strategies for elastic SDFs. A user study with spreadsheet users compares the human experience of programming with elastic SDFs to the alternative of relying on array-processing combinators. Our user study finds that the cognitive load of elastic SDFs is lower than for SDFs with map/reduce array combinators, the closest alternative solution.

In this paper we investigate the effectiveness of functional language features when writing scientific codes. Our programs are written in the purely functional subset of Id and executed on a one node Motorola Monsoon machine, and in Haskell and executed on a Sparc 2. In the application we study – the NAS FT benchmark, a three-dimensional heat equation solver – it is necessary to target and select one-dimensional sub-arrays in three-dimensional arrays. Furthermore, it is important to be able to share computation in array definitions. We compare first order and higher order implementations of this benchmark. The higher order version uses functions to select one-dimensional sub-arrays, or slices, from a three-dimensional object, whereas the first order version creates copies to achieve the same result. We compare various representations of a three-dimensional object, and study the effect of strictness in Haskell. We also study the performance of our codes when employing recursive and iterative implementations of the one-dimensional FFT, which forms the kernel of this benchmark. It turns out that these languages still have quite inefficient implementations, with respect to both space and time. For the largest problem we could run (323), Haskell is 15 times slower than Fortran and uses three times more space than is absolutely necessary, whereas Id on Monsoon uses nine times more cycles than Fortran on the MIPS R3000, and uses five times more space than is absolutely necessary. This code, and others like it, should inspire compiler writers to improve the performance of functional language implementations.

We introduce a typed λ-calculus which allows the use of exceptions in the ML style. It is an extension of the system $AF_2$ of Krivine & Leivant (Krivine, 1990; Leivant, 1983). We show its main properties: confluence, strong normalization and weak subject reduction. The system satisfies the “the proof as program” paradigm as in $AF_2$. Moreover, the underlined logic of our system is intuitionistic logic.

Haskell code is developed for two ways to list the strings of the language defined by a regular expression: directly by set operations and indirectly by converting to and simulating an equivalent automaton. The exercise illustrates techniques for dealing with infinite ordered domains and leads to an effective standard form for nondeterministic finite automata.

This paper addresses the issue of analysing the run-time behaviour of lazy, higher-order functional programs. We examine the difference between the way that functional programmers and functional language implementors view program behaviour. Existing profiling techniques are discussed and a new technique is proposed which produces results that are straightforward for programmers to assimilate. The new technique, which we call lexical profiling, collects information about the run-time behaviour of functional programs, and reports the results with respect to the original source code rather than simply listing the actions performed at run-time. Lexical profiling complements implementation-specific profiling and is important because it provides a view of program activity which is largely independent of the underlying evaluation mechanism. Using the lexical profiler, programmers may easily relate results back to the source program. We give a full implementation of the lexical profiling technique for a sequential, interpretive graph reduction engine, and extensions for compiled and parallel graph reduction are discussed.

Polytypic programming is a way of defining type-indexed operations, such as map, fold and zip, based on type information. Run-time polytypic programming allows that type information to be dynamically computed – this support is essential in modern programming languages that support separate compilation, first-class type abstraction, or polymorphic recursion. However, in previous work we defined run-time polytypic programming with a type-passing semantics. Although it is natural to define polytypic programs as operating over first-class types, such a semantics suffers from a number of drawbacks. This paper describes how to recast that work in a type-erasure semantics, where terms represent type information in a safe manner. The resulting language is simple and easy to implement – we present a prototype implementation of the necessary machinery as a small Haskell library.

Dependently typed programming advocates the use of various indexed versions of the same shape of data, but the formal relationship amongst these structurally similar datatypes usually needs to be established manually and tediously. Ornaments have been proposed as a formal mechanism to manage the relationships between such datatype variants. In this paper, we conduct a case study under an ornament framework; the case study concerns programming binomial heaps and their operations — including insertion and minimum extraction — by viewing them as lifted versions of binary numbers and numeric operations. We show how current dependently typed programming technology can lead to a clean treatment of the binomial heap constraints when implementing heap operations. We also identify some gaps between the current technology and an ideal dependently typed programming language that we would wish to have for our development.

The following three figures (figures 10, 11 and 12) were not shown in the original published version of the article. These figures constitute the entire static semantics of the STAL type system.

We show how the binary encoding and decoding of typed data and typed programs can be understood, programmed and verified with the help of question–answer games. The encoding of a value is determined by the yes/no answers to a sequence of questions about that value; conversely, decoding is the interpretation of binary data as answers to the same question scheme. We introduce a general framework for writing and verifying game-based codecs. We present games in Haskell for structured, recursive, polymorphic and indexed types, building up to a representation of well-typed terms in the simply-typed λ-calculus with polymorphic constants. The framework makes novel use of isomorphisms between types in the definition of games. The definition of isomorphisms together with additional simple properties make it easy to prove that codecs derived from games never encode two distinct values using the same code, never decode two codes to the same value and interpret any bit sequence as a valid code for a value or as a prefix of a valid code. Formal properties of the framework have been proved using the Coq proof assistant.

We develop a methodology for writing interactive and object-based programs (in the sense of Wegner) in dependently typed functional programming languages. The methodology is implemented in the ooAgda library. ooAgda provides a syntax similar to the one used in object-oriented programming languages, thanks to Agda's copattern matching facility. The library allows for the development of graphical user interfaces (GUIs), including the use of action listeners.

Our notion of interactive programs is based on the IO monad defined by Hancock and Setzer, which is a coinductive data type. We use a sized coinductive type which allows us to write corecursive programs in a modular way. Objects are server-side interactive programs that respond to method calls by giving answers and changing their state. We introduce two kinds of objects: simple objects and IO objects. Methods in simple objects are pure, while method calls in IO objects allow for interactions before returning their result. Our approach also allows us to extend interfaces and objects by additional methods.

We refine our approach to state-dependent interactive programs and objects through which we can avoid exceptions. For example, with a state-dependent stack object, we can statically disable the pop method for empty stacks. As an example, we develop the implementation of recursive functions using a safe stack. Using a coinductive notion of object bisimilarity, we verify basic correctness properties of stack objects and show the equivalence of different stack implementations. Finally, we give a proof of concept that our interaction model allows to write GUI programs in a natural way: we present a simple drawing program, and a program which allows the users to move a small spaceship using a button.

We present a short and direct syntactic proof of the fact that adding the axiom of choice and the principle of excluded-middle to Coquand–Huet's Calculus of Constructions gives proof-irrelevance.

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.

Kamareddine, F., & Ríos (1997) conjecture that the λse-calculus preserves the strong normalisation of the λ-calculus. We prove here that this conjecture is false.

Proving bounds on the resource consumption of a program by statically analyzing its source code is an important and well-studied problem. Automatic approaches for numeric programs with side effects usually apply abstract interpretation-based invariant generation to derive bounds on loops and recursion depths of function calls. This article presents an alternative approach to resource-bound analysis for numeric and heap-manipulating programs that uses type-based amortized resource analysis. As a first step towards the analysis of imperative code, the technique is developed for a first-order ML-like language with unsigned integers and arrays. The analysis automatically derives bounds that are multivariate polynomials in the numbers and the lengths of the arrays in the input. Experiments with example programs demonstrate two main advantages of amortized analysis over current abstract interpretation–based techniques. For one thing, amortized analysis can handle programs with non-linear intermediate values like f((n + m)2). For another thing, amortized analysis is compositional and works naturally for compound programs like f(g(x)).

In this paper we present a notion of expansion of a term in the lambda-calculus which transforms terms into linear terms. This transformation replaces each occurrence of a variable in the original term by a fresh variable taking into account non-trivial implications in the structure of the term caused by these simple replacements. We prove that the class of terms which can be expanded is the same of terms typable in an Intersection Type System, i.e. the strongly normalizable terms. We then show that expansion is preserved by weak-head reduction, the reduction considered by functional programming languages.