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This is a personal recollection on the Move fire on May 13, 1985
In computer science, in the area of formal language theory, frequent use is made of a variety of string functions; however, the notation used is different from that used for computer programming, and some commonly used functions in the theoretical realm are rarely used when programming. This article defines some of these basic terms.
A string is a finite sequence of characters. The empty string is denoted by . The concatenation of two strings and is denoted by , or shorter by . Concatenating with the empty string makes no difference: . Concatenation of strings is associative: .
For example, .
A language is a finite or infinite set of strings. Besides the usual set operations like union, intersection etc., concatenation can be applied to languages: if both and are languages, their concatenation is defined as the set of concatenations of any string from and any string from , formally . Again, the concatenation dot is often omitted for brevity.
The language consisting of just the empty string is to be distinguished from the empty language . Concatenating any language with the former doesn't make any change: , while concatenating with the latter always yields the empty language: . Concatenation of languages is associative: .
For example, abbreviating , the set of all three-digit decimal numbers is obtained as . The set of all decimal numbers of arbitrary length is an example for an infinite language.
The alphabet of a string is the set of all of the characters that occur in a particular string. If s is a string, its alphabet is denoted by
The alphabet of a language is the set of all characters that occur in any string of , formally: .
For example, the set is the alphabet of the string , and the above is the alphabet of the above language as well as of the language of all decimal numbers.
Let L be a language, and let Σ be its alphabet. A string substitution or simply a substitution is a mapping f that maps characters in Σ to languages (possibly in a different alphabet). Thus, for example, given a character a ∈ Σ, one has f(a)=La where La ⊆ Δ* is some language whose alphabet is Δ. This mapping may be extended to strings as
for the empty string ε, and
for string s ∈ L and character a ∈ Σ. String substitutions may be extended to entire languages as [1]
Regular languages are closed under string substitution. That is, if each character in the alphabet of a regular language is substituted by another regular language, the result is still a regular language.[2] Similarly, context-free languages are closed under string substitution.[3][note 1]
A simple example is the conversion fuc(.) to uppercase, which may be defined e.g. as follows:
| character | mapped to language | remark |
|---|---|---|
| x | fuc(x) | |
| ‹a› | { ‹A› } | map lowercase char to corresponding uppercase char |
| ‹A› | { ‹A› } | map uppercase char to itself |
| ‹ß› | { ‹SS› } | no uppercase char available, map to two-char string |
| ‹0› | { ε } | map digit to empty string |
| ‹!› | { } | forbid punctuation, map to empty language |
| ... | similar for other chars |
For the extension of fuc to strings, we have e.g.
For the extension of fuc to languages, we have e.g.
A string homomorphism (often referred to simply as a homomorphism in formal language theory) is a string substitution such that each character is replaced by a single string. That is, , where is a string, for each character .[note 2][4]
String homomorphisms are monoid morphisms on the free monoid, preserving the empty string and the binary operation of string concatenation. Given a language , the set is called the homomorphic image of . The inverse homomorphic image of a string is defined as
while the inverse homomorphic image of a language is defined as
In general, , while one does have
and
for any language .
The class of regular languages is closed under homomorphisms and inverse homomorphisms.[5] Similarly, the context-free languages are closed under homomorphisms[note 3] and inverse homomorphisms.[6]
A string homomorphism is said to be ε-free (or e-free) if for all a in the alphabet . Simple single-letter substitution ciphers are examples of (ε-free) string homomorphisms.
An example string homomorphism guc can also be obtained by defining similar to the above substitution: guc(‹a›) = ‹A›, ..., guc(‹0›) = ε, but letting guc be undefined on punctuation chars. Examples for inverse homomorphic images are
For the latter language, guc(guc−1({ ‹A›, ‹bb› })) = guc({ ‹a› }) = { ‹A› } ≠ { ‹A›, ‹bb› }. The homomorphism guc is not ε-free, since it maps e.g. ‹0› to ε.
A very simple string homomorphism example that maps each character to just a character is the conversion of an EBCDIC-encoded string to ASCII.
If s is a string, and is an alphabet, the string projection of s is the string that results by removing all characters that are not in . It is written as . It is formally defined by removal of characters from the right hand side:
Here denotes the empty string. The projection of a string is essentially the same as a projection in relational algebra.
String projection may be promoted to the projection of a language. Given a formal language L, its projection is given by
The right quotient of a character a from a string s is the truncation of the character a in the string s, from the right-hand side. It is denoted as . If the string does not have a on the right hand side, the result is the empty string. Thus:
The quotient of the empty string may be taken:
Similarly, given a subset of a monoid , one may define the quotient subset as
Left quotients may be defined similarly, with operations taking place on the left of a string.[citation needed]
Hopcroft and Ullman (1979) define the quotient L1/L2 of the languages L1 and L2 over the same alphabet as L1/L2 = { s | ∃t∈L2. st∈L1 }.[7] This is not a generalization of the above definition, since, for a string s and distinct characters a, b, Hopcroft's and Ullman's definition implies yielding {}, rather than { ε }.
The left quotient (when defined similar to Hopcroft and Ullman 1979) of a singleton language L1 and an arbitrary language L2 is known as Brzozowski derivative; if L2 is represented by a regular expression, so can be the left quotient.[8]
The right quotient of a subset of a monoid defines an equivalence relation, called the right syntactic relation of S. It is given by
The relation is clearly of finite index (has a finite number of equivalence classes) if and only if the family of right quotients is finite; that is, if
is finite. In the case that M is the monoid of words over some alphabet, S is then a regular language, that is, a language that can be recognized by a finite-state automaton. This is discussed in greater detail in the article on syntactic monoids.[citation needed]
The right cancellation of a character a from a string s is the removal of the first occurrence of the character a in the string s, starting from the right-hand side. It is denoted as and is recursively defined as
The empty string is always cancellable:
Clearly, right cancellation and projection commute:
The prefixes of a string is the set of all prefixes to a string, with respect to a given language:
where .
The prefix closure of a language is
Example:
A language is called prefix closed if .
The prefix closure operator is idempotent:
The prefix relation is a binary relation such that if and only if . This relation is a particular example of a prefix order.[citation needed]
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In computer science, in the area of formal language theory, frequent use is made of a variety of string functions; however, the notation used is different from that used for computer programming, and some commonly used functions in the theoretical realm are rarely used when programming. This article defines some of these basic terms.
In computer science, a suffix tree (also called PAT tree or, in an earlier form, position tree) is a compressed trie containing all the suffixes of the given text as their keys and positions in the text as their values. Suffix trees allow particularly fast implementations of many important string operations. The construction of such a tree for the string S {\displaystyle S} takes time and space linear in the length of S {\displaystyle S} . Once constructed, several operations can be performed quickly, such as locating a substring in S {\displaystyle S} , locating a substring if a certain number of mistakes are allowed, and locating matches for a regular expression pattern. Suffix trees also provided one of the first linear-time solutions for the longest common substring problem. These speedups come at a cost: storing a string's suffix tree typically requires significantly more space than storing the string itself.
Icon is a very high-level programming language based on the concept of "goal-directed execution" in which an expression in code returns "success" along with a result, or a "failure", indicating that there is no valid result. The success and failure of a given expression is used to direct further processing, whereas conventional languages would typically use Boolean logic written by the programmer to achieve the same ends. Because the logic for basic control structures is often implicit in Icon, common tasks can be completed with less explicit code. Icon was designed by Ralph Griswold after leaving Bell Labs where he was a major contributor to the SNOBOL language. SNOBOL was a string-processing language with what would be considered dated syntax by the standards of the early 1970s. After moving to the University of Arizona, he further developed the underlying SNOBOL concepts in SL5, but considered the result to be a failure. This led to the significantly updated Icon, which blends the short but conceptually dense code of SNOBOL-like languages with the more familiar syntax of ALGOL-inspired languages like C or Pascal. Like the languages that inspired it, the primary area of use of Icon is managing strings and textual patterns. String operations often fail, for instance, finding "the" in "world". In most languages, this requires testing and branching to avoid using a non-valid result. In Icon most of these sorts of tests are simply unneeded, reducing the amount of code that must be written. Complex pattern handling can be done in a few lines of terse code, similar to more dedicated languages like Perl but retaining a more function-oriented syntax familiar to users of other ALGOL-like languages. Icon is not object-oriented, but an object-oriented extension named Idol was developed in 1996 which eventually became Unicon. It also inspired other languages, with its simple generators being especially influential; Icon's generators were a major inspiration for the Python language.
A suffix is part of a word; an affix that follows the morphemes to which it can attach. Possessive suffix, a suffix used in word formation for creation of various possessive forms Suffix may also refer to: Suffix (name), the style at the end of a person's name which gives additional identifying information about the person Suffix (computer science), the last part of a string of characters Suffix notation, a notation for manipulating vector quantities, also known as index notation Suffix array, an array of integers giving the starting positions of suffixes of a string in lexicographical order Suffix tree, a data structure that presents the suffixes of a given string in a way that allows for a particularly fast implementation of many important string operations
Before the 1921 destruction of Tulsa’s Greenwood District, Black residents had created a remarkable center of business and community life. The district included stores, professional offices, entertainment venues and homes owned by Black citizens. Understanding Greenwood means learning what was built—not only what was burned.
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