DCGs + Memoing = Packrat Parsing but Is It Worth It?

Becket, Ralph; Somogyi, Zoltán

doi:10.1007/978-3-540-77442-6_13

Cited by 17 publications

(23 citation statements)

References 6 publications

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“…As practitioners' experiences increase, they increasingly question whether the cost of memorization is justified by its benefits. Supplementally, there are many claims in the literature [1], [9], [11], such that plain recursive descent parsers are sufficiently competitive, or even faster than packrat parsers.…”

Section: Preliminary Investigationmentioning

confidence: 99%

“…In Refs. [1], [5], there is a little confusion on the choice of nonterminals. For example, the Spacing rule is regarded as transient, which means no need for memoization in Ref.…”

Section: Effectiveness Of Memoizationmentioning

confidence: 99%

“…However, as Table 3 indicates, the Spacing rule shows the second best utilization. The heuristic analysis based on the properties of a defined grammar is not so easy, and prone to error [1].…”

Section: Effectiveness Of Memoizationmentioning

confidence: 99%

“…In cases of parsing C source code, despite a fact that we can observe significantly increased backtracking activity, a plain parser still shows very competitive performance compared to a packrat parser. The advantage 1 Yokohama National University, Yokohama, Kanagawa 240-8501, Japan a) kimio@ynu.ac.jp of packrat parsing is still questionable if we take its huge memory consumption into consideration.…”

Section: Introductionmentioning

confidence: 99%

“…As many researchers have claimed [1], [9], [11], exponential behavior does not seem to happen in practice. However, our experience suggested that the claim is not true in some closed visible examples.…”

Section: Introductionmentioning

confidence: 99%

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Packrat Parsing with Elastic Sliding Window

Kuramitsu

2015

Journal of Information Processing

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Packrat parsing is a linear-time implementation method of recursive descent parsers. The trick is a memoization mechanism, where all parsing results are memorized to avoid redundant parsing in cases of backtracking. An arising problem is extremely huge heap consumption in memoization, resulting in the fact that the cost of memoization is likely to outweigh its benefits. In many cases, developers need to make a difficult choice to abandon packrat parsing despite the possible exponential time parsing. Elastic packrat parsing is developed in order to avoid such a difficult choice. The heap consumption is upper-bounded since memorized results are stored on a sliding window buffer. In addition, the buffer capacity is adjusted by tracing each of nonterminal backtracking activities at runtime. Elastic packrat parsing is implemented in a part of our Nez parser. We demonstrate that the elastic packrat parsing achieves stable and robust performance against a variety of inputs with different backtracking activities.

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Section: Preliminary Investigationmentioning

confidence: 99%

“…In Refs. [1], [5], there is a little confusion on the choice of nonterminals. For example, the Spacing rule is regarded as transient, which means no need for memoization in Ref.…”

Section: Effectiveness Of Memoizationmentioning

confidence: 99%

Section: Effectiveness Of Memoizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Packrat Parsing with Elastic Sliding Window

Kuramitsu

2015

Journal of Information Processing

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Adaptable Parsing Expression Grammars

Reis

Bigonha

Iorio

et al. 2012

Programming Languages

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Parser generators have been used for more than 50 years. Tools like YACC can automatically build a parser from a formal definition of the syntax of a language, usually based on context-free grammars (CFG). The main motivation for automatic parser generation is compiler correctness and recognition completeness, since with manual implementation it is very difficult to guarantee that all programs in a given language will be correctly analysed. Despite the advantagens mentioned above, the technology of automatic parser generation is still not available for languages that allow on-the-fly modifications on their own set of grammar rules. There is a lack of appropriate formal models for describing the syntax of these languages, therefore efficient parsers may not be automatically generated, requiring handwritten code. In this thesis, we present the design and formal definition of Adaptable Parsing Expression Grammars (APEG), an extension to the Parsing Expression Grammar (PEG) model that allows the modification of production rules during the analysis of an input string. We also show that APEG is capable to define languages that require on-the-fly modifications and allows automatic generation of parsers that are reasonably efficient to be used in practice.

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The computational power of parsing expression grammars

Loff

Moreira

Reis

2020

Journal of Computer and System Sciences

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We study the computational power of parsing expression grammars (PEGs). We begin by constructing PEGs with unexpected behaviour, and surprising new examples of languages with PEGs, including the language of palindromes whose length is a power of two, and a binary-counting language.We then propose a new computational model, the scaffolding automaton, and prove that it exactly characterises the computational power of parsing expression grammars (PEGs).Several consequences will follow from this characterisation: (1) we show that PEGs are computationally "universal", in a certain sense, which implies the existence of a PEG for a P-complete language; (2) we show that there can be no pumping lemma for PEGs; and (3) we show that PEGs are strictly more powerful than online Turing machines which do o(n/ log n) steps of computation per input symbol.

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DCGs + Memoing = Packrat Parsing but Is It Worth It?

Cited by 17 publications

References 6 publications

Packrat Parsing with Elastic Sliding Window

Packrat Parsing with Elastic Sliding Window

Adaptable Parsing Expression Grammars

The computational power of parsing expression grammars

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