A Scheme letrec expression is easily converted into more primitive constructs via a straightforward transformation given in the Revised5 Report. This transformation, unfortunately, introduces assignments that can impede the generation of efficient code. This article presents a more judicious transformation that preserves the semantics of the revised report transformation and also detects invalid references and assignments to left-hand-side variables, yet enables the compiler to generate efficient code. A variant of letrec that enforces left-to-right evaluation of bindings is also presented and shown to add virtually no overhead.

Program specialization is a program transformation methodology which improves program efficiency by exploiting the information about the input data which are available at compile time. We show that current techniques for program specialization based on partial evaluation do not perform well on nondeterministic logic programs. We then consider a set of transformation rules which extend the ones used for partial evaluation, and we propose a strategy for guiding the application of these extended rules so to derive very efficient specialized programs. The efficiency improvements which sometimes are exponential, are due to the reduction of nondeterminism and to the fact that the computations which are performed by the initial programs in different branches of the computation trees, are performed by the specialized programs within single branches. In order to reduce nondeterminism we also make use of mode information for guiding the unfolding process. To exemplify our technique, we show that we can automatically derive very efficient matching programs and parsers for regular languages. The derivations we have performed could not have been done by previously known partial evaluation techniques.

Formal specifications of software systems are extremely useful because they can be rigorously analyzed, verified, and validated, giving high confidence that the specification captures the desired behavior. To transfer this confidence to the actual source code implementation, a formal link is needed between the specification and the implementation. Generating the implementation directly from the specification provides one such link. A program transformation system such as Paige's APTS can be useful in developing a source code generator. This paper describes a case study in which APTS was used to produce code generators that construct C source code from a requirements specification in the SCR (Software Cost Reduction) tabular notation. In the study, two different code generation strategies were explored. The first strategy uses rewrite rules to transform the parse tree of an SCR specification into a parse tree for the corresponding C code. The second strategy associates a relation with each node of the specification parse tree. Each member of this relation acts as an attribute, holding the C code corresponding to the tree at the associated nodes the root of the tree has the entire C program as its member of the relation. This paper describes the two code generators supported by APTS, how each was used to synthesize code for two example SCR requirements specifications, and what was learned about APTS from these implementations.

We propose an axiomatization of fixpoint operators in typed call-by-value programming languages, and give its justifications in two ways. First, it is shown to be sound and complete for the notion of uniform T-fixpoint operators of Simpson and Plotkin. Second, the axioms precisely account for Filinski's fixpoint operator derived from an iterator (infinite loop constructor) in the presence of first-class continuations, provided that we define the uniformity principle on such an iterator via a notion of effect-freeness (centrality). We then explain how these two results are related in terms of the underlying categorical structures.

Incremental computation takes advantage of repeated computations on inputs that differ slightly from one another, computing each output efficiently by exploiting the previous output. This paper gives an overview of a general and systematic approach to incrementalization: given a program f and an operation ⊕, the approach yields an incremental program that computes f(x ⊕ y) efficiently by using the result of f(x), the intermediate results of f(x), and auxiliary information of f(x) that can be inexpensively maintained. Since every non-trivial computation proceeds by iteration or recursion, the approach can be used for achieving efficient computation by computing each iteration incrementally using an appropriate incremental program. This approach has applications in interactive systems, optimizing compilers, transformational programming, and many other areas, where problems were previously solved in less general and systematic ways. This paper also describes the design and implementation of CACHET, a prototype system for incrementalization.

In collaboration with his colleagues at Oxford, Christopher Strachey pioneered the analysis of programming languages in terms of semantic features. Three of Strachey's contributions—inductive definition of semantics, semantic-domain definitions, and calculi for semantic description—are presented, and their consequences on languages research are described. Strachey's impact, present and future, on the computer programming “mainstream” is also outlined.