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Abstract. Landin’s SECD machine was the first abstract machine for applicative expressions, i.e., functional programs. Landin’s J operator was the first control operator for functional languages, and was specified by an extension of the SECD machine. We present a family of evaluation functions corresponding to this extension of the SECD machine, using a series of elementary transformations (transformation into continuation-passing style (CPS) and defunctionalization, chiefly) and their left inverses (transformation into direct style and refunctionalization). To this end, we modernize the SECD machine into a bisimilar one that operates in lockstep with the original one but that (1) does not use a data stack and (2) uses the caller-save rather than the callee-save convention for environments. We also identify that the dump component of the SECD machine is managed in a callee-save way. The caller-save counterpart of the modernized SECD machine precisely corresponds to Thielecke’s doublebarrelled continuations and to Felleisen’s encoding of J in terms of call/cc. We then variously characterize the J operator in terms of CPS and in terms of delimited-control operators in the CPS hierarchy. As a byproduct, we also present several reduction semantics for applicative expressions

Higher-order program transformations raise new challenges for proving properties of their output, since they resist traditional, rst-order proof techniques. In this work, we consider (1) the \one-pass" continuationpassing style (CPS) transformation, which is second-order, and (2) the occurrences of parameters of continuations in its output. To this end, we specify the one-pass CPS transformation relationally and we use the proof technique of logical relations.

. We illustrate a simple and e#ective solution to semantics-based compiling. Our solution is based on "type-directed partial evaluation", and -- our compiler generator is expressed in a few lines, and is e#cient; -- its input is a well-typed, purely functional definitional interpreter in the style of denotational semantics; -- the output of the generated compiler is e#ectively three-address code, in the fashion and e#ciency of the Dragon Book; -- the generated compiler processes several hundred lines of source code per second. The source language considered in this case study is imperative, blockstructured, higher-order, call-by-value, allows subtyping, and obeys stack discipline. It is bigger than what is usually reported in the literature on semantics-based compiling and partial evaluation. Our compiling technique uses the first Futamura projection, i.e., we compile programs by specializing a definitional interpreter with respect to the program. Specialization is carri...

Plotkin, in his seminal article Call-by-name, call-by-value and the λ-calculus, formalized evaluation strategies and simulations using operational semantics and continuations. In particular, he showed how call-by-name evaluation could be simulated under call-by-value evaluation and vice versa. Since Algol 60, however, call-by-name is both implemented and simulated with thunks rather than with continuations. We recast

One of the flagship applications of partial evaluation is compilation and compiler generation. However, partial evaluation is usually expressed as a source-to-source transformation for high-level languages, whereas realistic compilers produce object code. We close this gap by composing a partial evaluator with a compiler by automatic means. Our work is a successful application of several meta-computation techniques to build the system, both in theory and in practice. The composition is an application of deforestation or fusion. The result is a run-time code generation system built from existing components. Its applications are numerous. For example, it allows the language designer to perform interpreter-based experiments with a source-to-source version of the partial evaluator before building a realistic compiler which generates object code automatically.

Abstract. To introduce the republication of “Definitional Interpreters for Higher-Order Programming Languages”, the author recounts the circumstances of its creation, clarifies several obscurities, corrects a few mistakes, and briefly summarizes some more recent developments.

A substantial amount of work has been devoted to the proof of correctness of various program analyses but much less attention has been paid to the correctness of compiler optimisations based on these analyses. In this paper we tackle the problem in the context of strictness analysis for lazy functional languages. We show that compiler optimisations based on strictness analysis can be expressed formally in the functional framework using continuations. This formal presentation has two benefits: it allows us to give a rigorous correctness proof of the optimised compiler; and it exposes the various optimisations made possible by a strictness analysis. 1 Introduction Realistic compilers for imperative or functional languages include a number of optimisations based on non-trivial global analyses. Proving the correctness of such optimising compilers can be done in three steps: 1. proving the correctness of the original (unoptimised) compiler; Correspondence regarding this paper should be ...

Compilers for higher-order programming languages like Scheme, ML, and Lisp can be broadly characterized as either "direct compilers" or "continuation-passing style (CPS) compilers", depending on their main intermediate representation. Our central result is a precise correspondence between the two compilation strategies. Starting from

. Proving the congruence between a direct semantics and a continuation semantics is often surprisingly complicated considering that direct-style -terms can be transformed into continuation style automatically. However, transforming the representation of a direct-style semantics into continuation style usually does not yield the expected representation of a continuation-style semantics (i.e., one written by hand). The goal of our work is to automate the transformation between textual representations of direct semantics and of continuation semantics. Essentially, we identify properties of a direct-style representation (e.g., totality), and we generalize the transformation into continuation style accordingly. As a result, we can produce the expected representation of a continuation semantics, automatically. It is important to understand the transformation between representations of direct and of continuation semantics because it is these representations that get processed in any kind of ...