Partial evaluation of pattern matching in strings

Consel, Charles; Danvy, Olivier

doi:10.1016/0020-0190(89)90113-0

Cited by 77 publications

(65 citation statements)

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“…some known input data. A classical example is the specialization of a (semi)naive pattern matcher for a fixed pattern into an efficient algorithm-sometimes called "the KMP-test" (Ager et al, 2002;Consel and Danvy, 1989). The considered program is as follows: …”

Section: Program Specializationmentioning

confidence: 99%

Cost-Augmented Partial Evaluation of Functional Logic Programs

Vidal

2004

Higher-Order and Symbolic Computation

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Abstract. We enhance the narrowing-driven partial evaluation scheme for lazy functional logic programs with the computation of symbolic costs. The enhanced scheme allows us to estimate the effects of the program transformer in a precise framework and, moreover, to quantify these effects. The considered costs are "symbolic" in the sense that they measure the number of basic operations performed during a computation rather than actual execution times. Our scheme may serve as a basis to develop speedup analyses and cost-guided transformers. A cost-augmented partial evaluator, which demonstrates the usefulness of our approach, has been implemented in the multi-paradigm language Curry.

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Section: Program Specializationmentioning

confidence: 99%

Cost-Augmented Partial Evaluation of Functional Logic Programs

Vidal

2004

Higher-Order and Symbolic Computation

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“…1 Subsequently, Consel and Danvy pointed out that a binding-time improved (i.e., staged) quadratic string matcher could also be specialized into a linear string matcher, using a standard, Mix-style partial evaluator [7]. A number of publications followed, showing either a range of binding-time improved string matchers or presenting a range of partial evaluators integrating the binding-time improvement [1,9,11,12,15,23,24,25].…”

Section: List Of Figuresmentioning

confidence: 99%

“…We relate the original KMP algorithm [18] to a staged quadratic string matcher that keeps one character of negative information (essentially Consel and Danvy's original solution [7]; there are many ways to stage a string matcher [1,13], and we show one in Appendix A). Our approach is semantic rather than algorithmic or intuitive:…”

Section: This Workmentioning

confidence: 99%

On Obtaining Knuth, Morris, and Pratt's String Matcher by Partial Evaluation

Ager¹,

Danvy²,

Rohde³

2002

BRICS

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We present the first formal proof that partial evaluation of a quadratic string matcher can yield the precise behaviour of Knuth, Morris, and Pratt's linear string matcher.Obtaining a KMP-like string matcher is a canonical example of partial evaluation: starting from the naive, quadratic program checking whether a pattern occurs in a text, one ensures that backtracking can be performed at partial-evaluation time (a binding-time shift that yields a staged string matcher); specializing the resulting staged program yields residual programs that do not back up on the text,à la KMP. We are not aware, however, of any formal proof that partial evaluation of a staged string matcher precisely yields the KMP string matcher, or in fact any other specific string matcher.In this article, we present a staged string matcher and we formally prove that it performs the same sequence of comparisons between pattern and text as the KMP string matcher. To this end, we operationally specify each of the programming languages in which the matchers are written, and we formalize each sequence of comparisons with a trace semantics. We also state the (mild) conditions under which specializing the staged string matcher with respect to a pattern string provably yields a specialized string matcher whose size is proportional to the length of this pattern string and whose time complexity is proportional to the length of the text string. Finally, we show how tabulating one of the functions in this staged string matcher gives rise to the 'next' table of the original KMP algorithm.The method scales for obtaining other linear string matchers, be they known or new. * Extended version of an article

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“…2) with respect to a fixed pattern we show that perfect driving coupled with a simple folding strategy obtains the efficiency of a matcher generated by the Knuth, Morris & Pratt (KMP) al gorithm [15]. This effect is achieved without the need for an 'insightful reprogramming' of the naive matcher as necessary for partial evaluation [5,11]. The complexity of the specialized algorithm is O (n), where n is the length of the string.…”

Section: Perfect Driving Of a Naive Pattern Matchermentioning

confidence: 99%

“…A partial evaluator can achieve the same non-trivial result after identifying static components in the naive matcher and reprogramming the subject program [5,11]. Clearly, doing this by using an "automatic insight" frees the user from performing such subtle tasks.…”

Section: Related Workmentioning

confidence: 99%

Occam's razor in metacomputation: the notion of a perfect process tree

Glück

Klimov

1993

Static Analysis

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Abstract. We introduce the notion of a perfect process tree as a model for the full prop agation of in forma tion in metacomputation. Starting with constant propagation we construct step-by-step the driving mechanism used in su percompila tion which ensures the perfect propagation of information. The concept of a simple super compil er based on perfect driving coupled with a simple folding strategy is explained. As an example we demonstrate that specializing a naive pattern matcher with respect to a fixed pattern obtains the efficiency of a matcher generated by the Knuth, Morris & Pratt al gorithm.

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Partial evaluation of pattern matching in strings

Cited by 77 publications

References 1 publication

Cost-Augmented Partial Evaluation of Functional Logic Programs

Cost-Augmented Partial Evaluation of Functional Logic Programs

On Obtaining Knuth, Morris, and Pratt's String Matcher by Partial Evaluation

Occam's razor in metacomputation: the notion of a perfect process tree

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