In this paper we present a language for programming with higher-order modules. The language HML is based on Standard ML in that it provides structures, signatures and functors. In HML, functors can be declared inside structures and specified inside signatures; this is not possible in Standard ML. We present an operational semantics for the static semantics of HML signature expressions, with particular emphasis on the handling of sharing. As a justification for the semantics, we prove a theorem about the existence of principal signatures. This result is closely related to the existence of principal type schemes for functional programming languages with polymorphism.

A functional approach presents a fresh perspective on the problem of animation. We present an implementation of a functional animation system written in Haskell, and illustrate how it may be used to create simple and colourful animations.

We take Abramsky's term assignment for Intuitionistic Linear Logic (the linear term calculus) as the basis of a functional programming language. This is a language where the programmer must embed explicitly the resource and control information of an algorithm. We give a type reconstruction algorithm for our language in the style of Milner's W algorithm, together with a description of the implementation and examples of use.

The Flagship Project1 was a research collaboration between the University of Manchester, Imperial College London and International Computers Ltd. The project was unusual in that it aimed to produce a complete computing system based on a declarative programming style. Three areas of a declarative system were addressed: (1) programming languages and programming environments; (2) the machine architecture and computational models; and (3) the software environment. This overview paper discusses each of these areas, the intention being to present the project as a coherent whole.

Lazy functional languages have non-strict semantics and are purely declarative, i.e. they support the notion of referential transparency and are devoid of side-effects. Traditional debugging techniques are, however, not suited for lazy functional languages, since computations generally do not take place in the order one might expect. Since algorithmic debugging allows the user to concentrate on the declarative aspects of program semantics, and will semi-automatically find functions containing bugs, we propose to use this technique for debugging lazy functional programs. Because of the non-strict semantics of lazy functional languages, arguments to functions are in general partially evaluated expressions. The user is, however, usually more concerned with the values that these expressions represent. We address this problem by providing the user with a strictified view of the execution trace whenever possible. In this paper, we present an algorithmic debugger for a lazy functional language based on strictification and some experience in using it. A number of problems with the current implementation of the debugger (e.g. too large trace size and too many questions asked) are also discussed and some techniques for overcoming these problems, at least partially, are suggested. The key techniques are immediate strictification and piecemeal tracing.

We analyse the computational complexity of type inference for untyped λ-terms in the second-order polymorphic typed λ-calculus (F2) invented by Girard and Reynolds, as well as higher-order extensions F3, F4, …, Fω proposed by Girard. We prove that recognising the F2-typable terms requires exponential time, and for Fω the problem is non-elementary. We show as well a sequence of lower bounds on recognising the Fk-typable terms, where the bound for Fk+1 is exponentially larger than that for Fk.

The lower bounds are based on generic simulation of Turing Machines, where computation is simulated at the expression and type level simultaneously. Non-accepting computations are mapped to non-normalising reduction sequences, and hence non-typable terms. The accepting computations are mapped to typable terms, where higher-order types encode reduction sequences, and first-order types encode the entire computation as a circuit, based on a unification simulation of Boolean logic. A primary technical tool in this reduction is the composition of polymorphic functions having different domains and ranges.

These results are the first nontrivial lower bounds on type inference for the Girard/Reynolds system as well as its higher-order extensions. We hope that the analysis provides important combinatorial insights which will prove useful in the ultimate resolution of the complexity of the type inference problem.

We present the complete development, in Gallina, of the residual theory of β-reduction in pure λ-calculus. The main result is the Prism Theorem, and its corollary Lévy's Cube Lemma, a strong form of the parallel-moves lemma, itself a key step towards the confluence theorem and its usual corollaries (Church-Rosser, uniqueness of normal forms). Gallina is the specification language of the Coq Proof Assistant (Dowek et al., 1991; Huet 1992b). It is a specific concrete syntax for its abstract framework, the Calculus of Inductive Constructions (Paulin-Mohring, 1993). It may be thought of as a smooth mixture of higher-order predicate calculus with recursive definitions, inductively defined data types and inductive predicate definitions reminiscent of logic programming. The development presented here was fully checked in the current distribution version Coq V5.8. We just state the lemmas in the order in which they are proved, omitting the proof justifications. The full transcript is available as a standard library in the distribution of Coq.

In this paper we present an equivalence between TIM, a machine developed to implement non-strict functional programming languages, and the set of Categorical Multi-Combinators, a rewriting system developed with similar aims. These two models of computation at first appear to be quite different, but we show a direct equivalence between them, thereby adding some new structure to the ‘design-space’ of abstract machines for non-strict languages.

Unfolding is a common technique in program transformations. Here, we present a computation model where unfolding is a simple generalisation of the usual concept of evaluation. The model is a variant of the well-known full substitution evaluation rule for recursive programs. The evaluation mechanism involved is symbolic substitution of function definitions followed by simplification. Simplification is expressed as a confluent rewrite strategy which uses three kinds of reductions: β-reduction, non-erasing reduction, and erasing reduction. Non-erasing reductions include simplification of constant subexpressions. Erasing reductions formalize the behaviour of nonstrict operations. In this computation model, we prove a termination theorem of symbolic unfolding relative to more instantiated calls. A possible application of the model is a technique called total unfolding, where a partially instantiated function call is unfolded until no more calls exist. Under certain conditions the result will be a first order term: such terms correspond to basic blocks in imperative programs and can be efficiently implemented by scheduling techniques. Possible applications are hardware synthesis, and code generation for parallel machines.

To illuminate the fundamental concepts involved in object-oriented programming languages, we describe the design of TOOPL, a paradigmatic, statically-typed, functional, object-oriented programming language which supports classes, objects, methods, hidden instance variables, subtypes and inheritance.

It has proven to be quite difficult to design such a language which has a secure type system. A particular problem with statically type checking object-oriented languages is designing typechecking rules which ensure that methods provided in a superclass will continue to be type correct when inherited in a subclass. The type-checking rules for TOOPL have this feature, enabling library suppliers to provide only the interfaces of classes with actual executable code, while still allowing users to safely create subclasses. To achieve greater expressibility while retaining type-safety, we choose to separate the inheritance and subtyping hierarchy in the language.

The design of TOOPL has been guided by an analysis of the semantics of the language, which is given in terms of a model of the F-bounded second-order lambda calculus with fixed points at both the element and type level. This semantics supports the language design by providing a means to prove that the type-checking rules are sound, thus guaranteeing that the language is type-safe.

While the semantics of our language is rather complex, involving fixed points at both the element and type level, we believe that this reflects the inherent complexity of the basic features of object-oriented programming languages. Particularly complex features include the implicit recursion inherent in the use of the keyword, self, to refer to the current object, and its corresponding type, MyType. The notions of subclass and inheritance introduce the greatest semantic complexities, whereas the notion of subtype is more straightforward to deal with. Our semantic investigations lead us to recommend caution in the use of inheritance, since small changes to method definitions in subclasses can result in major changes to the meanings of the other methods of the class.

Many of the details that a programmer must manage when programming in a procedural language are handled by the implementation in a functional language. In a parallel functional language, we would expect the assignment of processes to processors and the scheduling of processes to be handled by the implementation. The partitioning of a program into processes may be handled by the implementation as well.

We will assume that a parallel functional program may create processes dynamically, and that processes may synchronize in an arbitrary manner. It does not matter whether processes are defined in the source program or generated by the implementation.

On parallel systems where each processor has some local memory, it is common practice not to move processes once they have started to execute. We will show that if each process must be executed on a single processor, then no fully automatic scheduling strategy can ensure good performance.

We also will show that if all processes are sequential processes (i.e. do not contain internal parallelism), and if a process may be moved whenever it resumes execution following synchronization with another process, then good performance can be assured, at least in theory.

Self-applicable specializers have been used successfully to automate the generation of compilers. Specializers are often rather sophisticated, for which reason one would like to adapt and transform them with the aid of the computer. But how to automate this process? The answer to this question is given by three specializer projections. While the Futamura projections define the generation of compilers from interpreters, the specializer projections define the generation of specializers from interpreters. We discuss the potential applications of the specializer projections, and argue that their realization is a real touchstone for the effectiveness of the specialization principle. In particular, we discuss generic specializers, bootstrapping of subject languages and the generation of optimizing specializers from interpretive specifications. The Futamura projections are regarded as a special case of the specializer projections. Recent results confirm that the specializer projections can be performed in practice using partial evaluators.

We develop a formal, type-theoretic account of the basic mechanisms of object-oriented programming: encapsulation, message passing, subtyping and inheritance. By modelling object encapsulation in terms of existential types instead of the recursive records used in other recent studies, we obtain a substantial simplification both in the model of objects and in the underlying typed λ-calculus.

We present here a generalization of A-translation to a class of pure type systems. We apply this translation to give a direct proof of the existence of a looping combinator in a large class of inconsistent type systems, a class which includes type systems with a type of all types. This is the first non-automated solution to this problem.

Large functional programs are often constructed by decomposing each big task into smaller tasks which can be performed by simpler functions. This hierarchical style of developing programs has been found to improve programmers' productivity because smaller functions are easier to construct and reuse. However, programs written in this way tend to be less efficient. Unnecessary intermediate data structures may be created. More function invocations may be required.

To reduce such performance penalties, Phil Wadler proposed a transformation algorithm, called deforestation, which could automatically fuse certain composed expressions together to eliminate intermediate tree-like data structures. However, his technique is currently safe (terminates with no loss of efficiency) for only a subset of first-order expressions.

This paper will generalise the deforestation technique to make it safe for all first-order and higher-order functional programs. Our generalisation is explained using a model for safe fusion which views each function as a producer and its parameters as consumers. Through this model, syntactic program properties are proposed to classify producers and consumers as either safe or unsafe. This classification is used to identify sub-terms that can be safely fused/eliminated. We present the generalised transformation algorithm, illustrate it with examples and provide a termination proof for the transformation algorithm of first-order programs. This paper also contains a suite of additional techniques to further improve the basic safe fusion method. These improvements could be viewed as enhancements to compensate for some inadequacies of the syntactic analyses used.

Baby Modula-3 is a small, functional, object-oriented programming language. It is intended as a vehicle for explaining the core of Modula-3 from a biased perspective: Baby Modula-3 includes the main features of Modula-3 related to objects, but not much else. To the theoretician, Baby Modula-3 provides a tractable, concrete example of an object-oriented language, and we use it to study the formal semantics of objects. Baby Modula-3 is defined with a structured operational semantics and with a set of static type rules. A denotational semantics guarantees the soundness of this definition.