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In computer science a context-free grammar
(CFG) is a formal grammar in which every production
rule is of the form
- V → w
where V is a non-terminal symbol and w is a string consisting of terminals and/or non-terminals. The term
"context-free" comes from the feature that the variable V can always be replaced by w, in no matter what context it
occurs. A formal language is context-free if there
is a context-free grammar which generates it.
Context-free grammars are important because they are powerful enough to describe the syntax of programming languages; in fact, almost all programming languages
are defined via context-free grammars. On the other hand, context-free grammars are simple enough to allow the construction of
efficient parsing algorithms which for a given string determine whether and how it can be generated from the grammar. See
Earley parser, LR parser
and LL parser.
BNF (Backus-Naur Form) is often used to express context-free
grammars.
Examples
Example 1
A simple context-free grammar is
- S → aSb | ε
where | is used to separate different options for the same non-terminal and ε stands for the empty string. This grammar
generates the language
which is not regular.
Example 2
Here is a context-free grammar for syntactically correct infix algebraic expressions in the variables x, y and z:
- S → x | y | z | S + S | S - S | S * S | S/S | (S)
This grammar can for example generate the string "( x + y ) * x - z * y / ( x + x )".
Example 3
A context-free grammar for the language consisting of all strings over {a,b} which contain a different number of a's than b's
is
- S → U | V
- U → TaU | TaT
- V → TbV | TbT
- T → aTbT | bTaT | ε
Here, T can generate all strings with the same number of a's as b's, U generates all strings with more a's than b's and V
generates all strings with fewer a's than b's.
Other examples
Context-free grammars are not limited in application to mathematical ("formal") languages. The ancient Indian linguist
Panini described Sanskrit using a
context-free grammar. Recently, it has been suggested that a class of Tamil poetry called Venpa is governed by a context-free grammar.
Derivations and Syntax trees
There are basically two ways to describe how in a certain grammar a string can be derived from the start symbol. The simplest
way is to list the consecutive strings of symbols, beginning with the start symbol and ending with the string, and the rules that
have been applied. If we introduce a strategy such as "always replace the left-most nonterminal first" then for context-free
grammars the list of applied grammar rules is by itself sufficient. This is called the leftmost derivation of a string.
For example, if we take the following grammar:
- (1) S → S + S
- (2) S → 1
and the string "1 + 1 + 1" then the left derivation of this string is the list [ (1), (1), (2), (2), (2) ]. Analogously the
rightmost derivation is defined as the list that we get if we always replace the rightmost nonterminal first. In this
case this would be the list [ (1), (2), (1), (2), (2)].
The distinction between leftmost derivation and rightmost derivation is important because in most parsers the transformation of the input is defined by giving a piece of code for every grammar rule that is
executed whenever the rule is applied. Therefore it is important to know whether the parser determines a leftmost or a rightmost
derivation because this determines the order in which the pieces of code will be executed. See for an example LL parsers and LR parsers.
A derivation also imposes in some sense a hierarchical structure on the string that is derived. For example the structure of
the string "1 + 1 + 1" would, according to the leftmost derivation, be:
- S→S+S (1)
- S→S+S+S (1)
- S→1+S+S (2)
- S→1+1+S (2)
- S→1+1+1 (2)
- { { { 1 }S + { 1 }S }S + { 1 }S }S
where { ... }S indicates a substring recognized as belonging to S. This hierarchy can also be seen as a tree:
S
/|\
/ | \
/ | \
S '+' S
/|\ |
/ | \ |
S '+' S '1'
| |
'1' '1'
This tree is called a concrete syntax tree (see also abstract syntax tree) of the string. In this case the presented leftmost and the rightmost derivation
define the same syntax tree, however there is another (leftmost) derivation of the same string possible
- S→ S + S (1)
- S→ 1 + S (2)
- S→ 1 + S + S (1)
- S→ 1 + 1 + S (2)
- S→ 1 + 1 + 1 (2)
and this defines the following syntax tree:
S
/|\
/ | \
/ | \
S '+' S
| /|\
| / | \
'1' S '+' S
| |
'1' '1'
If for certain strings in the language of the grammar there are more than one parsing tree then the grammar is said to be an
ambiguous grammar. Such grammars are usually hard to parse because the parser cannot always decide which grammar rule it
has to apply.
Normal forms
Every context-free grammar which does not generate the empty string can be transformed into an equivalent one in Chomsky normal form or Greibach normal form. "Equivalent" here means that the two grammars generate the same language.
Because of the especially simple form of production rules in Chomsky Normal Form grammars, this normal form has both
theoretical and practical implications. For instance, given a context-free grammar, one can use the Chomsky Normal Form to
construct a polynomial-time algorithm which decides whether a given string is in the language represented by that grammar or not
(the CYK algorithm).
Properties of context-free languages
- An alternative and equivalent definition of context-free languages employs non-deterministic push-down automata: a language is context-free if and only if it can
be accepted by such an automaton.
- The union and concatenation of two context-free languages is context-free; the intersection need not be.
- The reverse of a context-free language is context-free, but the complement need not be.
- Every regular language is context-free because it can be
described by a regular grammar.
- The intersection of a context-free language and a regular language is always context-free.
- There exist context-sensitive languages
which are not context-free.
- To prove that a given language is not context-free, one employs the pumping lemma for context-free languages.
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