Context-free language: Difference between revisions
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Determining an instance of the [[membership problem]]; i.e. given a string <math>w</math>, determine whether <math>w \in L(G)</math> where <math>L</math> is the language generated by a given grammar <math>G</math>; is also known as ''recognition''. Context-free recognition for [[Chomsky normal form]] grammars was shown by [[Leslie Valiant|Leslie G. Valiant]] to be reducible to Boolean [[matrix multiplication]], thus inheriting its complexity upper bound of [[Big O notation|''O'']](''n''<sup>2.3728596</sup>).<ref>{{cite journal |first=Leslie G. |last=Valiant |title=General context-free recognition in less than cubic time |journal=Journal of Computer and System Sciences |date=April 1975 |volume=10 |number=2 |pages=308–315 |doi=10.1016/s0022-0000(75)80046-8 |doi-access=free |url=https://figshare.com/articles/journal_contribution/General_context-free_recognition_in_less_than_cubic_time/6605915/1/files/12096398.pdf }}</ref><ref group=note>In Valiant's paper, ''O''(''n''<sup>2.81</sup>) was the then-best known upper bound. See [[Matrix multiplication#Computational complexity]] for bound improvements since then.</ref> | Determining an instance of the [[membership problem]]; i.e. given a string <math>w</math>, determine whether <math>w \in L(G)</math> where <math>L</math> is the language generated by a given grammar <math>G</math>; is also known as ''recognition''. Context-free recognition for [[Chomsky normal form]] grammars was shown by [[Leslie Valiant|Leslie G. Valiant]] to be reducible to Boolean [[matrix multiplication]], thus inheriting its complexity upper bound of [[Big O notation|''O'']](''n''<sup>2.3728596</sup>).<ref>{{cite journal |first=Leslie G. |last=Valiant |title=General context-free recognition in less than cubic time |journal=Journal of Computer and System Sciences |date=April 1975 |volume=10 |number=2 |pages=308–315 |doi=10.1016/s0022-0000(75)80046-8 |doi-access=free |url=https://figshare.com/articles/journal_contribution/General_context-free_recognition_in_less_than_cubic_time/6605915/1/files/12096398.pdf }}</ref><ref group=note>In Valiant's paper, ''O''(''n''<sup>2.81</sup>) was the then-best known upper bound. See [[Matrix multiplication#Computational complexity]] for bound improvements since then.</ref> | ||
Conversely, [[Lillian Lee (computer scientist)|Lillian Lee]] has shown ''O''(''n''<sup>3−ε</sup>) Boolean matrix multiplication to be reducible to ''O''(''n''<sup>3−3ε</sup>) CFG parsing, thus establishing some kind of lower bound for the latter.<ref>{{cite journal |first=Lillian |last=Lee |author-link=Lillian Lee (computer scientist) |title=Fast Context-Free Grammar Parsing Requires Fast Boolean Matrix Multiplication |journal=J ACM |date=January 2002 |volume=49 |number=1 |pages=1–15 |url= | Conversely, [[Lillian Lee (computer scientist)|Lillian Lee]] has shown ''O''(''n''<sup>3−ε</sup>) Boolean matrix multiplication to be reducible to ''O''(''n''<sup>3−3ε</sup>) CFG parsing, thus establishing some kind of lower bound for the latter.<ref>{{cite journal |first=Lillian |last=Lee |author-link=Lillian Lee (computer scientist) |title=Fast Context-Free Grammar Parsing Requires Fast Boolean Matrix Multiplication |journal=J ACM |date=January 2002 |volume=49 |number=1 |pages=1–15 |url=https://www.cs.cornell.edu/home/llee/papers/bmmcfl-jacm.pdf |archive-url=https://web.archive.org/web/20030427152836/http://www.cs.cornell.edu/home/llee/papers/bmmcfl-jacm.pdf |archive-date=2003-04-27 |url-status=live |doi=10.1145/505241.505242 |arxiv=cs/0112018|s2cid=1243491 }}</ref> | ||
Practical uses of context-free languages require also to produce a derivation tree that exhibits the structure that the grammar associates with the given string. The process of producing this tree is called ''[[parsing]]''. Known parsers have a time complexity that is cubic in the size of the string that is parsed. | Practical uses of context-free languages require also to produce a derivation tree that exhibits the structure that the grammar associates with the given string. The process of producing this tree is called ''[[parsing]]''. Known parsers have a time complexity that is cubic in the size of the string that is parsed. | ||
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== Further reading == | == Further reading == | ||
* {{cite book |first1=Jean-Michel |last1=Autebert |first2=Jean |last2=Berstel |first3=Luc |last3=Boasson |url= | * {{cite book |first1=Jean-Michel |last1=Autebert |first2=Jean |last2=Berstel |first3=Luc |last3=Boasson |url=https://www-igm.univ-mlv.fr/~berstel/Articles/1997CFLPDA.pdf |archive-url=https://web.archive.org/web/20110516030515/http://www-igm.univ-mlv.fr/%7Eberstel/Articles/1997CFLPDA.pdf |archive-date=2011-05-16 |url-status=live |chapter=Context-Free Languages and Push-Down Automata |editor1=G. Rozenberg |editor2=A. Salomaa |title=Handbook of Formal Languages |volume=1 |publisher=Springer-Verlag |date=1997 |pages=111–174}} | ||
* {{cite book|first=Seymour |last=Ginsburg |author-link=Seymour Ginsburg | title = The Mathematical Theory of Context-Free Languages | year = 1966 | publisher = McGraw-Hill | location = New York, NY, USA}} | * {{cite book|first=Seymour |last=Ginsburg |author-link=Seymour Ginsburg | title = The Mathematical Theory of Context-Free Languages | year = 1966 | publisher = McGraw-Hill | location = New York, NY, USA}} | ||
* {{Sipser 1997|chapter='''2''': Context-Free Languages |pages=91-122}} | * {{Sipser 1997|chapter='''2''': Context-Free Languages |pages=91-122}} | ||
Latest revision as of 17:04, 17 September 2025
In formal language theory, a context-free language (CFL), also called a Chomsky type-2 language, is a language generated by a context-free grammar (CFG).
Context-free languages have many applications in programming languages, in particular, most arithmetic expressions are generated by context-free grammars.
Background
Context-free grammar
Different context-free grammars can generate the same context-free language. Intrinsic properties of the language can be distinguished from extrinsic properties of a particular grammar by comparing multiple grammars that describe the language.
Automata
The set of all context-free languages is identical to the set of languages accepted by pushdown automata, which makes these languages amenable to parsing. Further, for a given CFG, there is a direct way to produce a pushdown automaton for the grammar (and thereby the corresponding language), though going the other way (producing a grammar given an automaton) is not as direct.
Examples
An example context-free language is , the language of all non-empty even-length strings, the entire first halves of which are Template:Mvar's, and the entire second halves of which are Template:Mvar's. Template:Mvar is generated by the grammar . This language is not regular. It is accepted by the pushdown automaton where is defined as follows:[note 1]
Unambiguous CFLs are a proper subset of all CFLs: there are inherently ambiguous CFLs. An example of an inherently ambiguous CFL is the union of with . This set is context-free, since the union of two context-free languages is always context-free. But there is no way to unambiguously parse strings in the (non-context-free) subset which is the intersection of these two languages.Template:Sfn
Dyck language
The language of all properly matched parentheses is generated by the grammar .
Properties
Context-free parsing
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The context-free nature of the language makes it simple to parse with a pushdown automaton.
Determining an instance of the membership problem; i.e. given a string , determine whether where is the language generated by a given grammar ; is also known as recognition. Context-free recognition for Chomsky normal form grammars was shown by Leslie G. Valiant to be reducible to Boolean matrix multiplication, thus inheriting its complexity upper bound of O(n2.3728596).[1][note 2] Conversely, Lillian Lee has shown O(n3−ε) Boolean matrix multiplication to be reducible to O(n3−3ε) CFG parsing, thus establishing some kind of lower bound for the latter.[2]
Practical uses of context-free languages require also to produce a derivation tree that exhibits the structure that the grammar associates with the given string. The process of producing this tree is called parsing. Known parsers have a time complexity that is cubic in the size of the string that is parsed.
Formally, the set of all context-free languages is identical to the set of languages accepted by pushdown automata (PDA). Parser algorithms for context-free languages include the CYK algorithm and Earley's Algorithm.
A special subclass of context-free languages are the deterministic context-free languages which are defined as the set of languages accepted by a deterministic pushdown automaton and can be parsed by a LR(k) parser.[3]
See also parsing expression grammar as an alternative approach to grammar and parser.
Closure properties
The class of context-free languages is closed under the following operations. That is, if L and P are context-free languages, the following languages are context-free as well:
- the union of L and PTemplate:Sfn
- the reversal of LTemplate:Sfn
- the concatenation of L and PTemplate:Sfn
- the Kleene star of LTemplate:Sfn
- the image of L under a homomorphism Template:Sfn
- the image of L under an inverse homomorphism Template:Sfn
- the circular shift of L (the language )Template:Sfn
- the prefix closure of L (the set of all prefixes of strings from L)Template:Sfn
- the quotient L/R of L by a regular language RTemplate:Sfn
Nonclosure under intersection, complement, and difference
The context-free languages are not closed under intersection. This can be seen by taking the languages and , which are both context-free.[note 3] Their intersection is , which can be shown to be non-context-free by the pumping lemma for context-free languages. As a consequence, context-free languages cannot be closed under complementation, as for any languages A and B, their intersection can be expressed by union and complement: . In particular, context-free language cannot be closed under difference, since complement can be expressed by difference: .[4]
However, if L is a context-free language and D is a regular language then both their intersection and their difference are context-free languages.[5]
Decidability
In formal language theory, questions about regular languages are usually decidable, but ones about context-free languages are often not. It is decidable whether such a language is finite, but not whether it contains every possible string, is regular, is unambiguous, or is equivalent to a language with a different grammar.
The following problems are undecidable for arbitrarily given context-free grammars A and B:
- Equivalence: is ?Template:Sfn
- Disjointness: is ?Template:Sfn However, the intersection of a context-free language and a regular language is context-free,[6]Template:Sfn hence the variant of the problem where B is a regular grammar is decidable (see "Emptiness" below).
- Containment: is ?Template:Sfn Again, the variant of the problem where B is a regular grammar is decidable,Script error: No such module "Unsubst". while that where A is regular is generally not.Template:Sfn
- Universality: is ?Template:Sfn
- Regularity: is a regular language?Template:Sfn
- Ambiguity: is every grammar for ambiguous?Template:Sfn
The following problems are decidable for arbitrary context-free languages:
- Emptiness: Given a context-free grammar A, is ?Template:Sfn
- Finiteness: Given a context-free grammar A, is finite?Template:Sfn
- Membership: Given a context-free grammar G, and a word , does ? Efficient polynomial-time algorithms for the membership problem are the CYK algorithm and Earley's Algorithm.
According to Hopcroft, Motwani, Ullman (2003),[7] many of the fundamental closure and (un)decidability properties of context-free languages were shown in the 1961 paper of Bar-Hillel, Perles, and Shamir[8]
Languages that are not context-free
The set is a context-sensitive language, but there does not exist a context-free grammar generating this language.Template:Sfn So there exist context-sensitive languages which are not context-free. To prove that a given language is not context-free, one may employ the pumping lemma for context-free languages[8] or a number of other methods, such as Ogden's lemma or Parikh's theorem.[9]
Notes
References
Works cited
- Template:Hopcroft and Ullman 1979Template:Sfn whitelist
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Further reading
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- Template:Sipser 1997
Template:Navbox with columns Template:Authority control
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- ↑ Template:Harvtxt, p. 59, Theorem 6.7
- ↑ Script error: No such module "citation/CS1". Here: Sect.7.6, p.304, and Sect.9.7, p.411
- ↑ a b Script error: No such module "Citation/CS1".
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