Compiling Actions by Partial Evaluation, Revisited

Self Cite

Abstract. Type-directed partial evaluation stems from the residualization of arbitrary static values in dynamic contexts, given their type. Its algorithm coincides with t he o n e for coercing a s u btype value into a supertype value, which itself coincides with t he o n e of normalization in the -calculus. Type-directed partial evaluation is thus used to specialize compiled, closed programs, given their type. Since Similix, let-insertion is a cornerstone of partial evaluators for callby-value procedural programs with computational e ects. It prevents the duplication of residual computations, and more generally maintains the order of dynamic side e ects in residual programs. This article describes the extension of type-directed partial evaluation to insert residual let expressions. This extension requires the u s e r t o annotate a r r o w t ypes with e ect information. It is achieved by d elimiting and abstracting c o n trol, comparably to c o n tinuation-based specialization in direct style. It enables type-directed partial evaluation of e ectful programs (e.g., a d e nitional lambda-interpreter for an imperative l a n guage) that are in direct style. The residual programs are in A-normal form.

Section: Introductionmentioning

confidence: 58%

Online Type-Directed Partial Evaluation

Danvy¹

1997

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“…TDPE has been used for this purpose in several instances [4,5,11,12]. Having implemented the second Futamura projection, we can instead generate a compiler as the generating extension of an interpreter.…”

Section: Generating a Compiler For Tinymentioning

confidence: 99%

The Second Futamura Projection for Type-Directed Partial Evaluation

Grobauer¹,

Yang²

2000

A generating extension of a program specializes the program with respect to part of the input. Applying a partial evaluator to the program trivially yields a generating extension, but specializing the partial evaluator with respect to the program often yields a more efficient one. This specialization can be carried out by the partial evaluator itself; in this case, the process is known as the second Futamura projection.We derive an ML implementation of the second Futamura projection for Type-Directed Partial Evaluation (TDPE). Due to the differences between 'traditional', syntax-directed partial evaluation and TDPE, this derivation involves several conceptual and technical steps. These include a suitable formulation of the second Futamura projection and techniques for making TDPE amenable to self-application. In the context of the second Futamura projection, we also compare and relate TDPE with conventional offline partial evaluation.We demonstrate our technique with several examples, including compiler generation for Tiny, a prototypical imperative language.

“…The instantiation of height ge with these structures gives height . Applying the second Futamura projection as given in Equation 4 Figure 17: Instantiation via functors this purpose in several instances [5,6,10,11]. Having implemented the second Futamura projection, we can instead generate a compiler, which is the generating extension of an interpreter.…”

Section: Pragmaticsmentioning

confidence: 99%

The Second Futamura Projection for Type-Directed Partial Evaluation

Grobauer¹,

Yang²

1999

A generating extension of a program specializes it with respect to some specified part of the input. A generating extension of a program can be formed trivially by applying a partial evaluator to the program; the second Futamura projection describes the automatic generation of non-trivial generating extensions by applying a partial evaluator to itself with respect to the programs. We derive an ML implementation of the second Futamura projection for Type-Directed Partial Evaluation (TDPE). Due to the differences between `traditional', syntax-directed partial evaluation and TDPE, this derivation involves several conceptual and technical steps. These include a suitable formulation of the second Futamura projection and techniques for making TDPE amenable to self-application. In the context of the second Futamura projection, we also compare and relate TDPE with conventional offline partial evaluation. We demonstrate our technique with several examples, including compiler generation for Tiny, a prototypical imperative language.