Semantics-based compiling: A case study in type-directed partial evaluation

Danvy, Olivier; Vestergaard, René

doi:10.1007/3-540-61756-6_85

Cited by 24 publications

(11 citation statements)

References 14 publications

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“…Some inspiration for solving this exercise can be found in Danvy's lecture notes on type-directed partial evaluation [Dan98], in Grobauer and Yang's treatment of the second Futamura projection [GY01], and in Danvy and Vestergaard's take on semantics-based compiling by type-directed partial evaluation [DV96].…”

Section: Exercise 8 Extend the ML Implementation Of Tdpe With Disjoimentioning

confidence: 99%

Normalization and Partial Evaluation

Dybjer

Filinski

2002

Lecture Notes in Computer Science

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Abstract. We give an introduction to normalization by evaluation and type-directed partial evaluation. We first present normalization by evaluation for a combinatory version of Gödel System T. Then we show normalization by evaluation for typed lambda calculus with β and η conversion. Finally, we introduce the notion of binding time, and explain the method of type-directed partial evaluation for a small PCF-style functional programming language. We give algorithms for both call-by-name and call-by-value versions of this language.

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Section: Exercise 8 Extend the ML Implementation Of Tdpe With Disjoimentioning

confidence: 99%

Normalization and Partial Evaluation

Dybjer

Filinski

2002

Lecture Notes in Computer Science

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“…Typedirected partial evaluation, which we present next, has been investigated both practically [5,15,17,18,29,31,38] and foundationally [24,25,47].…”

Section: Background: Reduction-based Vs Reduction-free Normalizationmentioning

confidence: 99%

Memoization in Type-Directed Partial Evaluation

Balat

Danvy

2002

Generative Programming and Component Engineering

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Abstract. We use a code generator-type-directed partial evaluationto verify conversions between isomorphic types, or more precisely to verify that a composite function is the identity function at some complicated type. A typed functional language such as ML provides a natural support to express the functions and type-directed partial evaluation provides a convenient setting to obtain the normal form of their composition. However, off-the-shelf type-directed partial evaluation turns out to yield gigantic normal forms. We identify that this gigantism is due to redundancies, and that these redundancies originate in the handling of sums, which uses delimited continuations. We successfully eliminate these redundancies by extending type-directed partial evaluation with memoization capabilities. The result only works for pure functional programs, but it provides an unexpected use of code generation and it yields orders-of-magnitude improvements both in time and in space for type isomorphisms.

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“…These differences have contributed to the successful application of TDPE in various contexts, e.g., to perform semantics-based compilation [12]. An introductory account, as well as a survey of various treatments concerning NbE, can be found in Danvy's lecture notes [7].…”

Section: Role Of Typesmentioning

confidence: 99%

“…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

BRICS

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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.

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Semantics-based compiling: A case study in type-directed partial evaluation

Cited by 24 publications

References 14 publications

Normalization and Partial Evaluation

Normalization and Partial Evaluation

Memoization in Type-Directed Partial Evaluation

The Second Futamura Projection for Type-Directed Partial Evaluation

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