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Reviewer: Donald J. Bagert, Jr. In judging this work, it is important to take into account its intended audience: LR parsing has become a widely used method of .
Table of contents
- Re: What IS an LL/LR/SLR/LALR etc. grammar?
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- LR parser - Wikipedia
- ISBN 13: 9780521304139
- LR Parsing: Theory and Practice by Nigel P. Chapman, Hardcover | Barnes & Noble®.
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The data structures are updated during the processing of the input. Each state is associated with a unique situation. Upon reading a symbol a transition is made from one state to another, together with a possible update of the data structures and an emittance of output. The complexity of time and space of recognition, parsing and transduction can be studied more easily with the aid of automata.
Re: What IS an LL/LR/SLR/LALR etc. grammar?
Commonly, the lexical scanner, the lexicon and the parser operate in different linguistic layers. This may cause troubles with multiword s and words that appear in the grammar itself. A typical aspect of practical Document and Language Engineering is integrated error handling among all linguistic layers. Errors arise from ill-formed input and from wrong or inconsistent grammatical specifications. Linguists should be provided with a workbench for the development of lingware.
A process for recognition, parsing or transduction may be embedded within other processes. The theory of parser generation stems from computer science. LL bottom-up and LR top-down parsing have drawn a lot of attention because they cover most types of context-free grammars, while indeterminism of the parser may be resolved by lookahead. Parser generation involves a direct mapping of a grammar onto a stack automaton. Typical stages of the evolution of algorithms and programs are. The last approach is not mentioned by Jurafsky. This program may be embedded in another process, like an authors workbench.
We distinguish two situations.
The first one concerns a recognition process which generates a message when some point in the grammar is reached. The second one concerns a process where output-symbols are emitted.
This assumes that the output is of limited length. The input is potentially of unlimited length. In principle there is no upper bound for the guaranteed time. In a more colloquial definition of real-time the delay is, for human experience, ignorable. It emits output when the process is in a deterministic state. It emits output when a sentence is completed. This is attractive for the parsing of context-free grammars, because of the possibility of cubic processing time, e.
In that case a constraint to non-ambiguous grammars is frustrating. They may be minimized by maximizing the use of syntactic clues in the input, making use of lookahead. A grammar formalism together with the indefinite lookahead property provides for a context of indefinite size, to the left and to the right.
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This is in contrast with event-based formalisms. Most often asymptotic results are not only relevant to practice -- they are extremely relevant. Wikipedia pages for algorithms put the asymptotic complexities in special displays, and these displays are one of the first things that some practitioners look at. Since coming up with a theoretical model that is equivalent to "practical" is impossible, theoreticians often work like artillerists.
Artillerists often deliberately overshoot and undershoot, before they "fire for effect". But, nasty as these consequences could be, the advantage in accuracy is usually held to outweigh them. The practice of theoretical computer science is less risky, which makes "bracketing" a very attractive approach to tricky problems. Theoreticians often try to "bracket" practice between an "undershoot" and an "overshoot". The undershoots are models simple and efficient enough to be practical, but too weak to capture all the needs of practice.
The P vs.leondumoulin.nl/language/drama/cauchy3-book-31-poems-mad-as-nutty.php
LR parser - Wikipedia
NP problem is an active example of a bracketing technique. So P-hard is beyond any reasonable definition of "practical" -- it is an "overshoot". But the P vs. NP question is almost certainly very relevant to what is "practical". Resolving the P vs. NP question is likely to be an important or even necessary step. It is a mystery that such a seemingly obvious question has resisted the best efforts of the theoreticians for so long, and the solution of P vs.
NP is likely to bring new insights into asymptotic complexity. When Knuth published his , "practical parsing" was already bracketed. On the overshoot side, Irons had already published a parser for context-free grammars. Worst case, this ran in exponential time, and it was, and remains, expected that general context-free parsing was not going to be practical. On the undershoot side, there were regular expressions and recursive descent. Regular expressions are fast and very practical, but parse a very limited set of grammars. Recursive descent is also fast and, since it parses a larger set of grammars, was the closest undershoot.
To curry respect from the behaviourists, American linguistics for many years banned any reference to meaning. Behaviorists looked down on hypothesized mental states as not worthy of "science", and it's hard to have a theory of meaning without conjectures about mental states. Without mental states, language was just a set of utterances.
So in the linguist Leonard Bloomfield dutifully defined a "language" as a set of "utterances" for our purposes, "strings" , and through the 30s and 40s most American linguists followed him. After a brief nod to this tradition, Noam Chomsky restored sanity to linguistics. But it was too late for computer science. Automata theory adopted the semantics-free definition. In , Knuth inherited a lot of prior work, almost all of which ignored, not just meaning or semantics, but even syntax and structure. Knuth, of course, wanted to make contact with prior art.
The definition he had inherited seemed to work well enough and Knuth's defines a language as a set of strings. Most subsequent work has refused to breach this tradition. So the parsing theorists and everybody else had two different definitions of language.
But parsing theory also hoped to produce results relevant to practice, and few people are interested in recognizing meaningless strings -- almost everybody who parses is interested in at a minimum finding some kind of structure in what they parse, in order to do something with the result of the parse. Parsing theorists ended up using the word "language" in one sense, but implying that results they found worked for the word "language" in the usual sense. At this point both senses of the word "language" have gotten entrenched in parsing theory.
ISBN 13: 9780521304139
Instead of making up a new terminology for this blog post, I will borrow a distinction from linguistics and speak of the extension of a language and the intension of a language. The intension of a language, for our purposes here, can be regarded as its BNF grammar. Each language intension will have if it is well-defined exactly one extension. But multiple language intensions can have the same extension.
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The temptation to use language extensions as a proxy for LR -grammars must have been overwhelming. It turns out that the language extension of deterministic stack machines is exactly that of the LR grammars. Further, the language extension of the context-free grammars is exactly that of the non-deterministic stack machines. Borchardt Library, Melbourne Bundoora Campus. Monash University Library. The University of Melbourne Library. University of Sydney Library.
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