This survey presents information concerning the use of functional languages (both strict and non-strict) for teaching in higher education. It lists the languages used by over 70 different institutions, the years in which the courses are given, and the recommended textbooks.

We give a direct type-theoretic characterization of the basic mechanisms of object-oriented programming, including objects, methods, message passing, and subtyping, by introducing an explicit constructor for object types and suitable introduction, elimination, and equality rules. The resulting abstract framework provides a basis for justifying and comparing previous encodings of objects based on recursive record types (Cardelli, 1984; Cardelli, 1992; Bruce, 1994; Cook et al., 1990; Mitchell, 1990a) and encodings based on existential types (Pierce & Turner, 1994).

We present purely functional implementations of queues and double-ended queues (deques) requiring only O(1) time per operation in the worst case. Our algorithms are considerably simpler than previous designs with the same bounds. The inspiration for our approach is the incremental behaviour of certain functions on lazy lists.

Solid modelling using constructive solid geometry (CSG) includes many examples of stylised divide-and-conquer algorithms. We identify the sources of these recurrent patterns and describe a Geometric Evaluation Library (GEL) which captures them as higher-order functions. This library then becomes the basis of developing CSG applications quickly and concisely. GEL is currently implemented as a set of separately compiled modules in the pure functional language Hope+. We evaluate our work in terms of performance and general applicability. We also assess the benefits of the functional paradigm in this domain and the merits of programming with a set of higher-order functions.

And Joktan begat Almodad, and Sheleph, and Hazarmaveth, and Jerah, and Handoram, and Uzal, and Diklah, and Obal, and Abimael, and Sheba, and Ophir, and Havilah, and Jobab: all these were the sons of Joktan.

— Genesis 10:26–29

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.

This paper makes a contribution to the refinement of systems which involve search by proposing a simple non-deterministic model for rule based transition systems and using this to define a meaning for rule based refinement which allows each stage of the software development path to be verified with respect to the previous stage. The proposal allows a system which involves search to be specified in terms of all the possible outcomes. Each stage of refinement will introduce complexity to the rules and therefore develop the search space in ever more sophisticated ways. At each stage of the refinement it will be possible to be precise about which collections of outcomes have been deleted, thereby achieving a verified (prototype) implementation.

We re-express Hudak and Young's higher-order strictness analysis for the untyped λ-calculus in a conceptually simpler and more semantically-based manner. We show our analysis to be a sound abstraction of Hudak and Young's which is also complete in a sense we make precise.

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.

In a functional program, a simple random number generator may generate a lazy list of random numbers. This is fine when the random numbers are consumed sequentially at a single point in the program. However, things are more complicated in a program where random numbers are used at many locations, such as in a large simulation. The programmer should not need to worry about providing separate generators with a unique seed at each point where random numbers are used. At the same time, the programmer should not need to coordinate the use of a single stream of random numbers in many parts of the program, which can be particularly difficult with lazy evaluation or parallel processing.

We discuss several techniques for distributing random numbers to various parts of a program, and some methods of allowing different program components to evaluate random numbers locally. We then propose a new approach in which a random number sequence can be split at a random point to produce a pair of random number sequences that can be used independently at different points in the computation.

The approach can also be used in distributed procedural programs, where it is desirable to avoid dealing with a single source of random numbers. The approach has the added advantage of producing repeatable results, as might be needed in debugging, for example.

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.

We show how improving values (Burton, 1991) can be extended to handle both upper and lower bounds. The result is a new data type, called improving intervals. We give a simple implementation of improving intervals that uses a list of successively tighter bounds to represent a value. A program using improving intervals can be evaluated as a parallel program using speculative evaluation. The utility of improving intervals is demonstrated through two programs: parallel alpha-beta and parallel branch-and-bound

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.

A generic functional program is one which is parameterised by datatype. By installing specific choices, for example lists or trees, different programs are obtained that are, nevertheless, abstractly the same. The purpose of this paper is to explore the possibility of deriving generic programs. Part of the theory of lists that deals with segments is recast as a theory about ‘segments’ in a wide class of datatypes, and then used to pose and solve a generic version of a well-known problem.