Algorithms for checking subtyping between recursive types lie at the core of many programming language implementations. But the fundamental theory of these algorithms and how they relate to simpler declarative specifications is not widely understood, due in part to the difficulty of the available introductions to the area. This tutorial paper offers an ‘end-to-end’ introduction to recursive types and subtyping algorithms, from basic theory to efficient implementation, set in the unifying mathematical framework of coinduction.

This paper serves as a self-contained, tutorial introduction to combinatory models of the untyped lambda calculus. We focus particularly on the interpretation of free variables. We argue that free variables should not be interpreted as elements in a model, as is usually done, but as indeterminates. We claim that the resulting interpretation is more natural and leads to a closer correspondence between models and theories. In particular, it solves the problem of the notorious ζ-rule, which asserts that equations should be preserved under binders, and which fails to be sound for the usual interpretation.

Intensional polymorphism, the ability to dispatch to different routines based on types at run time, enables a variety of advanced implementation techniques for polymorphic languages, including tag-free garbage collection, unboxed function arguments, polymorphic marshalling and attened data structures. To date, languages that support intensional polymorphism have required a type-passing (as opposed to type-erasure) interpretation where types are constructed and passed to polymorphic functions at run time. Unfortunately, type-passing suffers from a number of drawbacks: it requires duplication of run-time constructs at the term and type levels, it prevents abstraction, and it severely complicates polymorphic closure conversion. We present a type-theoretic framework that supports intensional polymorphism, but avoids many of the disadvantages of type passing. In our approach, run-time type information is represented by ordinary terms. This avoids the duplication problem, allows us to recover abstraction, and avoids complications with closure conversion. In addition, our type system provides another improvement in expressiveness; it allows unknown types to be refined in place, thereby avoiding certain beta-expansions required by other frameworks.

Binary search trees are old hat, aren't they? Search trees are routinely covered in introductory computer science classes and they are widely used in functional programming courses to illustrate the benefits of algebraic data types and pattern matching. And indeed, the operation of insertion enjoys a succinct and elegant functional formulation. Figure 1 contains the six-liner given in the language Haskell 98.

Alas, both succinctness and elegance are lost when it comes to implementing the dual operation of deletion, also shown in figure 1. Two additional helper functions are required causing the code size to double in comparison with insertion.

We systematically develop a functional program that solves the countdown problem, a numbers game in which the aim is to construct arithmetic expressions satisfying certain constraints. Starting from a formal specification of the problem, we present a simple but inefficient program that solves the problem, and prove that this program is correct. We then use program fusion to calculate an equivalent but more efficient program, which is then further improved by exploiting arithmetic properties.

This paper presents a new two-stage CPS algorithm. The first stage plants trivial partial continuations via a recursive-descent traversal and the second stage is a rewrite system that transforms all nontail calls into tail calls. The algorithm combines the metaphors of the Plotkin-style CPS transformation along with reduction in the λ-calculus.