We present the first formalization of implementation strategies for first-class continuations. The formalization hinges on abstract machines for continuation-passing style (CPS) programs with a special treatment for the current continuation, accounting for the essence of first-class continuations. These abstract machines are proven equivalent to a standard, substitution-based abstract machine. The proof techniques work uniformly for various representations of continuations. As a byproduct, we also present a formal proof of the two folklore theorems that one continuation identifier is enough for second-class continuations and that second-class continuations are stackable.

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.

Starting from a continuation-based interpreter for a simple logic programming language, propositional Prolog with cut, we derive the corresponding logic engine in the form of an abstract machine. The derivation originates in previous work (our article at PPDP 2003) where it was applied to the lambda-calculus. The key transformation here is Reynolds's defunctionalization that transforms a tail-recursive, continuation-passing interpreter into a transition system, i.e., an abstract machine. Similar denotational and operational semantics were studied by de Bruin and de Vink (their article at TAPSOFT 1989), and we compare their study with our derivation. Additionally, we present a direct-style interpreter of propositional Prolog expressed with control operators for delimited continuations.

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this article, we propose a treatment of environments and the mechanism by which they are reified and manipulated, that addresses these concerns. The language described below (Rascal) permits environments to be reified into data structures, and data structures to be reflected into environments, but gives users great flexibility to constrain the extent and scope of these processes. We argue that the techniques and operators developed define a cohesive basis for building largescale modular systems using reflective programming techniques.

We investigate call-by-value continuation-passing style transforms that pass two continuations. Altering a single variable in the translation of #-abstraction gives rise to di#erent control operators: first-class continuations; dynamic control; and (depending on a further choice of a variable) either the return statement of C; or Landin's J-operator. In each case there is an associated simple typing. For those constructs that allow upward continuations, the typing is classical, for the others it remains intuitionistic, giving a clean distinction independent of syntactic details. Moreover, those constructs that make the typing classical in the source of the CPS transform break the linearity of continuation use in the target.

interpretation and fixed-point computation . . . 71 5.1.2 The time-stamping technique . . . . . . . . . . . . . . . . 72 5.2 The time-stamps-based approximation algorithm . . . . . . . . . 73 5.2.1 A class of recursive equations . . . . . . . . . . . . . . . . 73 5.2.2 The intuition behind time stamps . . . . . . . . . . . . . 74 5.3 A formalization of the time-stamps-based algorithm . . . . . . . 75 5.3.1 State-passing recursive equations . . . . . . . . . . . . . . 75 5.3.2 Correctness . . . . . . . . . . . . . . . . . . . . . . . . . . 77 5.3.3 Complexity estimates . . . . . . . . . . . . . . . . . . . . 78 5.4 An extension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 5.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Appendix 5.A Operational specification . . . . . . . . . . . . . . . . . 81 6 Static Transition Compression 85 6.2 Source and target languages . . . . . . . . . . . . . . . . . . . . . 86 6.2.1 An unstructured target language . . . . . . . . . . . . . . 86 6.2.2 A structured source language . . . . . . . . . . . . . . . . 86 6.3 A context-insensitive translation . . . . . . . . . . . . . . . . . . 87 6.3.4 Chains of jumps . . . . . . . . . . . . . . . . . . . . . . . 91 6.4 Context awareness . . . . . . . . . . . . . . . . . . . . . . . . . . 92 6.4.1 Continuations and duplication . . . . . . . . . . . . . . . 92 6.4.2 Towards the right thing . . . . . . . . . . . . . . . . . . . 92 6.5 A context-sensitive translation . . . . . . . . . . . . . . . . . . . 93 6.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

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 ...