BTA Algorithms to ensure termination of off-line partial evaluation

Glenstrup, Arne John; Jones, Neil D.

doi:10.1007/3-540-62064-8_23

Cited by 19 publications

(17 citation statements)

References 6 publications

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“…(6) Computer-placed program annotations to guide transformation, for example, binding-time annotation [Bondorf 1991;Consel 1993;Consel and Danvy 1993;Glenstrup and Jones 1996;Glück et al 1995;Jones et al 1993;Hatcliff et al 1999;Thiemann 1997]. After annotation, transformation is fully automatic, requiring no human interaction.…”

Section: On the Meaning Of "Automatic" In Program Transformationmentioning

confidence: 99%

“…These termination properties are easier to state than to achieve, as there is an intrinsic conflict between demands for completeness and termination of the specializer. Nonetheless, significant progress has been made in the past few years [Das 1998;Das and Reps 1996;Glenstrup 1999;Glenstrup and Jones 1996;Song and Futamura 2000]. A key is carefully to select which parts of the program should be computed at specialization time.…”

Section: Desirable Properties Of a Partial Evaluatormentioning

confidence: 99%

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Termination analysis and specialization-point insertion in offline partial evaluation

Glenstrup

Jones

2005

ACM Trans. Program. Lang. Syst.

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Recent research suggests that the goal of fully automatic and reliable program generation for a broad range of applications is coming nearer to feasibility. However, several interesting and challenging problems remain to be solved before it becomes a reality. Solving them is also necessary, if we hope ever to elevate software engineering from its current state (a highly developed handiwork) into a successful branch of engineering, capable of solving a wide range of new problems by systematic, well-automated and well-founded methods.A key problem in all program generation is termination of the generation process. This article focuses on off-line partial evaluation and describes recent progress towards automatically solving the termination problem, first for individual programs, and then for specializers and "generating extensions," the program generators that most offline partial evaluators produce.The technique is based on size-change graphs that approximate the changes in parameter sizes at function calls. We formulate a criterion, bounded anchoring, for detecting parameters known to be bounded during specialization: a bounded parameter can act as an anchor for other parameters. Specialization points necessary for termination are computed by adding a parameter that tracks call depth, and then selecting a specialization point in every call loop where it is unanchored. By generalizing all unbounded parameters, we compute a binding-time division which together with the set of specialization points guarantees termination.Contributions of this article include a proof, based on the operational semantics of partial evaluation with memoization, that the analysis guarantees termination; and an in-depth description of safety of the increasing size approximation operator required for termination analysis in partial evaluation.Initial experiments with a prototype shows that the analysis overall yields binding-time divisions that can achieve a high degree of specialization, while still guaranteeing termination.The article ends with a list of challenging problems whose solution would bring the community closer to the goal of broad-spectrum, fully automatic and reliable program generation.

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Section: On the Meaning Of "Automatic" In Program Transformationmentioning

confidence: 99%

Section: Desirable Properties Of a Partial Evaluatormentioning

confidence: 99%

Termination analysis and specialization-point insertion in offline partial evaluation

Glenstrup

Jones

2005

ACM Trans. Program. Lang. Syst.

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“…23 The old BTA from [13] took 1 m 39 s (on a Linux server which should correspond roughly to 57 seconds on the MacBook Air used here). 24 Furthermore the generated annotation file is erroneous and could not be used for specialisation. With our new BTA a correct annotation is generated in less than half a second; the ensuing specialisation by logen took 2.4 s. The generated code is very similar to the one obtained using a manually constructed annotation in Section 3 of [26] or in [35].…”

Section: Scalability: Pic Emulator and Gödel Systemmentioning

confidence: 99%

“…The first attempts at ensuring (local) termination for offline partial evaluation were developed in [24] in the context of functional programming; the core ideas later evolved into the size-change principle. Regarding offline partial evaluation of logic programs, the closest previous work is that of Craig et al [13], which itself is a further development of Section 6 of [36].…”

Section: Related Workmentioning

confidence: 99%

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Fast offline partial evaluation of logic programs

Leuschel

Vidal

2014

Information and Computation

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One of the most important challenges in partial evaluation is the design of automatic methods for ensuring the termination of the process. In this work, we introduce sufficient conditions for the strong (i.e., independent of a computation rule) termination and quasi-termination of logic programs which rely on the construction of size-change graphs. We then present a fast binding-time analysis that takes the output of the termination analysis and annotates logic programs so that partial evaluation terminates. In contrast to previous approaches, the new binding-time analysis is conceptually simpler and considerably faster, scaling to medium-sized or even large examples.

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2012

Program Specialization

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BTA Algorithms to ensure termination of off-line partial evaluation

Cited by 19 publications

References 6 publications

Termination analysis and specialization-point insertion in offline partial evaluation

Termination analysis and specialization-point insertion in offline partial evaluation

Fast offline partial evaluation of logic programs

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