Programming language
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225975726
2008-07-16T08:06:55Z
Diego Moya
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/* Syntax */ Formal semantics should be linked, also
A '''programming language''' is an [[artificial language]] that can be used to control the behavior of a machine, particularly a [[computer]].<ref>[http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_detail.htm?csnumber=33636 ISO 5127]—Information and documentation—Vocabulary, clause 01.05.10, defines a programming language as: an artificial language for expressing programs</ref> Programming languages are defined by [[syntax|syntactic]] and [[semantic]] rules which describe their structure and meaning respectively. Many programming languages have some form of written specification of their syntax and semantics; some are defined only by an official implementation.
Programming languages are used to facilitate communication about the task of organizing and manipulating information, and to express [[algorithm]]s precisely. Some authors restrict the term "programming language" to those languages that can express ''all'' possible algorithms;<ref>In mathematical terms, this means the programming language is [[Turing-complete]] {{cite book | last=MacLennan | first=Bruce J. | title=Principles of Programming Languages | page=1 | publisher=Oxford University Press | year=1987 | id=ISBN 0-19-511306-3 }}</ref> sometimes the term "[[computer language]]" is used for more limited artificial languages.
{{Programming language lists}}
Thousands of different programming languages have been created so far,<ref>[[2006|As of May 2006]] [http://hopl.murdoch.edu.au/ The Encyclopedia of Computer Languages] by [[Murdoch University]], [[Australia]] lists 8512 computer languages.</ref> and new languages are created every year.
==Definitions==
Traits often considered important for constituting a programming language:
*''Function:'' A programming language is a language used to write [[computer program]]s, which involve a [[computer]] performing some kind of [[computation]]<ref>{{cite web|author=[[Association for Computing Machinery|ACM]] SIGPLAN|title=Bylaws of the Special Interest Group on Programming Languages of the Association for Computing Machinery|url=http://www.acm.org/sigs/sigplan/sigplan_bylaws.htm|accessdate=2006-06-19|year=2003}}, ''The scope of SIGPLAN is the theory, design, implementation, description, and application of computer programming languages - languages that permit the specification of a variety of different computations, thereby providing the user with significant control (immediate or delayed) over the computer's operation.''</ref> or [[algorithm]] and possibly control external devices such as [[Computer printer|printers]], robots,<ref name="robots">{{cite web|url=http://www.cs.brown.edu/people/tld/courses/cs148/02/programming.html |title=Programming Robots |accessdate=2006-09-23 |last=Dean |first=Tom |date= |year=2002 |work=Building Intelligent Robots |publisher=Brown University Department of Computer Science}}</ref> and so on.
*''Target:'' Programming languages differ from [[natural language]]s in that natural languages are only used for interaction between people, while programming languages also allow humans to communicate instructions to machines. Some programming languages are used by one device to control another. For example [[PostScript]] programs are frequently created by another program to control a [[computer printer]] or display.
*''Constructs:'' Programming languages may contain constructs for defining and manipulating [[data structure]]s or controlling the [[control flow|flow of execution]].
*''Expressive power:'' The [[theory of computation]] classifies languages by the computations they are capable of expressing. All [[Turing complete]] languages can implement the same set of [[algorithm]]s. [[SQL|ANSI/ISO SQL]] and [[Charity programming language|Charity]] are examples of languages that are not Turing complete yet often called programming languages.<ref>{{cite web | author=Digital Equipment Corporation | title=Information Technology - Database Language SQL (Proposed revised text of DIS 9075) | url=http://www.contrib.andrew.cmu.edu/~shadow/sql/sql1992.txt | work=ISO/IEC 9075:1992, Database Language SQL | accessmonthday=June 29 | accessyear=2006}}</ref><ref>{{cite web|author=The Charity Development Group|title=The CHARITY Home Page | url=http://pll.cpsc.ucalgary.ca/charity1/www/home.html | month=December|year=1996|accessdate=2006-06-29}}, ''Charity is a categorical programming language...'', ''All Charity computations terminate.''</ref>
Non-computational languages, such as [[markup language]]s like [[HTML]] or [[formal grammar]]s like [[Backus–Naur form|BNF]], are usually not considered programming languages. A programming language (which may or may not be Turing complete) may be embedded in these non-computational (host) languages.
==Purpose==
A prominent purpose of programming languages is to provide instructions to a computer. As such, programming languages differ from most other forms of human expression in that they require a greater degree of precision and completeness. When using a natural language to communicate with other people, human authors and speakers can be ambiguous and make small errors, and still expect their intent to be understood. However figuratively speaking, computers "do exactly what they are told to do", and cannot "understand" what code the programmer intended to write. The combination of the language definition, the [[computer program|program]], and the program's inputs must fully specify the external behavior that occurs when the program is executed.
Many languages have been designed from scratch, altered to meet new needs, combined with other languages, and eventually fallen into disuse. Although there have been attempts to design one "universal" computer language that serves all purposes, all of them have failed to be accepted in this role.<ref>IBM in first publishing PL/I, for example, rather ambitiously titled its manual ''The universal programming language PL/I'' (IBM Library; 1966). The title reflected IBM's goals for unlimited subsetting capability: ''PL/I is designed in such a way that one can isolate subsets from it satisfying the requirements of particular applications.'' ({{cite web | url=http://eom.springer.de/P/p072885.htm | title= Encyclopaedia of Mathematics » P » PL/I | work=SpringerLink | accessmonthday=June 29 | accessyear=2006}}). [[Ada programming language|Ada]] and [[UNCOL]] had similar early goals.</ref> The need for diverse computer languages arises from the diversity of contexts in which languages are used:
* Programs range from tiny scripts written by individual hobbyists to huge systems written by hundreds of programmers.
* Programmers range in expertise from novices who need simplicity above all else, to experts who may be comfortable with considerable complexity.
* Programs must balance speed, size, and simplicity on systems ranging from [[microcontroller]]s to [[supercomputer]]s.
* Programs may be written once and not change for generations, or they may undergo nearly constant modification.
* Finally, programmers may simply differ in their tastes: they may be accustomed to discussing problems and expressing them in a particular language.
One common trend in the development of programming languages has been to add more ability to solve problems using a higher level of [[Abstraction (computer science)|abstraction]]. The earliest programming languages were tied very closely to the underlying hardware of the computer. As new programming languages have developed, features have been added that let programmers express ideas that are more remote from simple translation into underlying hardware instructions. Because programmers are less tied to the complexity of the computer, their programs can do more computing with less effort from the programmer. This lets them write more functionality per time unit.<ref> Frederick P. Brooks, Jr.: ''The Mythical Man-Month,'' Addison-Wesley, 1982, pp. 93-94 </ref>
[[Natural language and computation|Natural language processor]]s have been proposed as a way to eliminate the need for a specialized language for programming. However, this goal remains distant and its benefits are open to debate. [[Edsger Dijkstra]] took the position that the use of a formal language is essential to prevent the introduction of meaningless constructs, and dismissed natural language programming as "foolish."<ref>Dijkstra, Edsger W. [http://www.cs.utexas.edu/users/EWD/transcriptions/EWD06xx/EWD667.html On the foolishness of "natural language programming."] EWD667.</ref> [[Alan Perlis]] was similarly dismissive of the idea.<ref>Perlis, Alan, [http://www-pu.informatik.uni-tuebingen.de/users/klaeren/epigrams.html Epigrams on Programming]. SIGPLAN Notices Vol. 17, No. 9, September 1982, pp. 7-13</ref>
==Elements==
===Syntax===
[[Image:Python add5 parse.svg|thumb|right|396px|[[Parse tree]] of Python code with inset tokenization]]
[[Image:Python add5 syntax.svg|thumb|right|292px|[[Syntax highlighting]] is often used to aid programmers in recognizing elements of source code. The language above is [[Python (programming language)|Python]].]]
A programming language's surface form is known as its [[syntax of programming languages|syntax]]. Most programming languages are purely textual; they use sequences of text including words, numbers, and punctuation, much like written natural languages. On the other hand, there are some programming languages which are more [[visual programming language|graphical]] in nature, using spatial relationships between symbols to specify a program.
The syntax of a language describes the possible combinations of symbols that form a syntactically correct program. The meaning given to a combination of symbols is handled by semantics (either [[Formal semantics of programming languages|formal]] or hard-coded in a [[Reference implementation (computing)|reference implementation]]). Since most languages are textual, this article discusses textual syntax.
Programming language syntax is usually defined using a combination of [[regular expression]]s (for [[lexical analysis|lexical]] structure) and [[Backus-Naur Form]] (for [[context-free grammar|grammatical]] structure). Below is a simple grammar, based on [[Lisp programming language|Lisp]]:
<code>
expression ::= atom | list<br/>
atom ::= number | symbol<br/>
number ::= [+-]?['0'-'9']+<br/>
symbol ::= ['A'-'Z'<nowiki>'</nowiki>a'-'z'].*<br/>
list ::= '(' expression* ')'<br/>
</code>
This grammar specifies the following:
* an ''expression'' is either an ''atom'' or a ''list'';
* an ''atom'' is either a ''number'' or a ''symbol'';
* a ''number'' is an unbroken sequence of one or more decimal digits, optionally preceded by a plus or minus sign;
* a ''symbol'' is a letter followed by zero or more of any characters (excluding whitespace); and
* a ''list'' is a matched pair of parentheses, with zero or more ''expressions'' inside it.
The following are examples of well-formed token sequences in this grammar: '<code>12345</code>', '<code>()</code>', '<code>(a b c232 (1))</code>'
Not all syntactically correct programs are semantically correct. Many syntactically correct programs are nonetheless ill-formed, per the language's rules; and may (depending on the language specification and the soundness of the implementation) result in an error on translation or execution. In some cases, such programs may exhibit [[undefined behavior]]. Even when a program is well-defined within a language, it may still have a meaning that is not intended by the person who wrote it.
Using [[natural language]] as an example, it may not be possible to assign a meaning to a grammatically correct sentence or the sentence may be false:
* "[[Colorless green ideas sleep furiously]]." is grammatically well-formed but has no generally accepted meaning.
* "John is a married bachelor." is grammatically well-formed but expresses a meaning that cannot be true.
The following C language fragment is syntactically correct, but performs an operation that is not semantically defined (because <tt>p</tt> is a [[null pointer]], the operations <tt>p->real</tt> and <tt>p->im</tt> have no meaning):
complex *p = NULL;
complex abs_p = sqrt (p->real * p->real + p->im * p->im);
The grammar needed to specify a programming language can be classified by its position in the [[Chomsky hierarchy]]. The syntax of most programming languages can be specified using a Type-2 grammar, i.e., they are [[context-free grammar]]s.<ref>{{cite book|author = [[Michael Sipser]] | year = 1997 | title = Introduction to the Theory of Computation | publisher = PWS Publishing | id = ISBN 0-534-94728-X}} Section 2.2: Pushdown Automata, pp.101–114.</ref>
===Static semantics===
The static semantics defines restrictions on the structure of valid texts that are hard or impossible to express in standard syntactic formalisms.<ref>{{cite book|last=Aaby|first=Anthony|title=Introduction to Programming Languages|year=2004|url=http://cs.wwc.edu/~aabyan/LN/PL/book/index.html}}</ref> The most important of these restrictions are covered by type systems.
===Type system===
{{details|Type system}}
{{details|Type safety}}
A type system defines how a programming language classifies values and expressions into ''types'', how it can manipulate those types and how they interact. This generally includes a description of the [[data structure]]s that can be constructed in the language. The design and study of type systems using formal mathematics is known as ''[[type theory]]''.
Internally, all [[data]] in modern digital computers are stored simply as zeros or ones ([[Binary numeral system|binary]]).
====Typed versus untyped languages====
A language is ''typed'' if the specification of every operation defines types of data to which the operation is applicable, with the implication that it is not applicable to other types.<ref name="typing">{{cite web | url=http://www.acooke.org/andrew/writing/lang.html#sec-types | author=Andrew Cooke | title=An Introduction to Programming Languages | accessmonthday=June 30 | accessyear=2006}}</ref> For example, "<code>this text between the quotes</code>" is a string. In most programming languages, dividing a number by a string has no meaning. Most modern programming languages will therefore reject any program attempting to perform such an operation. In some languages, the meaningless operation will be detected when the program is compiled ("static" type checking), and rejected by the compiler, while in others, it will be detected when the program is run ("dynamic" type checking), resulting in a runtime [[Exception handling|exception]].
A special case of typed languages are the ''single-type'' languages. These are often scripting or markup languages, such as [[Rexx]] or [[SGML]], and have only one data type — most commonly character strings which are used for both symbolic and numeric data.
In contrast, an ''untyped language'', such as most [[assembly language]]s, allows any operation to be performed on any data, which are generally considered to be sequences of bits of various lengths.<ref name="typing"/> High-level languages which are untyped include [[BCPL]] and some varieties of [[Forth (programming language)|Forth]].
In practice, while few languages are considered typed from the point of view of [[type theory]] (verifying or rejecting ''all'' operations), most modern languages offer a degree of typing.<ref name="typing"/> Many production languages provide means to bypass or subvert the type system.
====Static versus dynamic typing====
In ''[[static typing]]'' all expressions have their types determined prior to the program being run (typically at compile-time). For example, 1 and (2+2) are integer expressions; they cannot be passed to a function that expects a string, or stored in a variable that is defined to hold dates.<ref name="typing"/>
Statically-typed languages can be ''manifestly typed'' or ''[[type inference|type-inferred]]''. In the first case, the programmer must explicitly write types at certain textual positions (for example, at variable [[declaration (computer science)|declaration]]s). In the second case, the compiler ''infers'' the types of expressions and declarations based on context. Most mainstream statically-typed languages, such as [[C Plus Plus|C++]], [[C Sharp (programming language)|C#]] and [[Java (programming language)|Java]], are manifestly typed. Complete type inference has traditionally been associated with less mainstream languages, such as [[Haskell (programming language)|Haskell]] and [[ML programming language|ML]]. However, many manifestly typed languages support partial type inference; for example, [[Java (programming language)|Java]] and [[C Sharp (programming language)|C#]] both infer types in certain limited cases.<ref>Specifically, instantiations of [[generic programming|generic]] types are inferred for certain expression forms. Type inference in Generic Java—the research language that provided the basis for Java 1.5's bounded [[parametric polymorphism]] extensions—is discussed in two informal manuscripts from the [[Types mailing list]]: [http://www.seas.upenn.edu/~sweirich/types/archive/1999-2003/msg00849.html Generic Java type inference is unsound] ([[Alan Jeffrey]], 17 December 2001) and [http://www.seas.upenn.edu/~sweirich/types/archive/1999-2003/msg00921.html Sound Generic Java type inference] ([[Martin Odersky]], 15 January 2002). C#'s type system is similar to Java's, and uses a similar partial type inference scheme.</ref>
''Dynamic typing'', also called ''latent typing'', determines the type-safety of operations at runtime; in other words, types are associated with ''runtime values'' rather than ''textual expressions''.<ref name="typing"/> As with type-inferred languages, dynamically typed languages do not require the programmer to write explicit type annotations on expressions. Among other things, this may permit a single variable to refer to values of different types at different points in the program execution. However, type errors cannot be automatically detected until a piece of code is actually executed, making debugging more difficult. [[Ruby (programming language)|Ruby]], [[Lisp programming language|Lisp]], [[JavaScript]], and [[Python (programming language)|Python]] are dynamically typed.
====Weak and strong typing====
''Weak typing'' allows a value of one type to be treated as another, for example treating a string as a number.<ref name="typing"/> This can occasionally be useful, but it can also allow some kinds of program faults to go undetected at [[compile time]] and even at [[run time]].
''Strong typing'' prevents the above. An attempt to perform an operation on the wrong type of value raises an error.<ref name="typing"/> Strongly-typed languages are often termed ''type-safe'' or ''[[type safety|safe]]''.
An alternative definition for "weakly typed" refers to languages, such as [[Perl]], [[JavaScript]], and [[C++]], which permit a large number of implicit type conversions. In JavaScript, for example, the expression <code>2 * x</code> implicitly converts <code>x</code> to a number, and this conversion succeeds even if <code>x</code> is <code>null</code>, <code>undefined</code>, an <code>Array</code>, or a string of letters. Such implicit conversions are often useful, but they can mask programming errors.
''Strong'' and ''static'' are now generally considered orthogonal concepts, but usage in the literature differs. Some use the term ''strongly typed'' to mean ''strongly, statically typed'', or, even more confusingly, to mean simply ''statically typed''. Thus [[C (programming language)|C]] has been called both strongly typed and weakly, statically typed.<ref>{{cite web | url=http://www.schemers.org/Documents/Standards/R5RS/HTML/r5rs-Z-H-4.html | title=Revised Report on the Algorithmic Language Scheme (February 20, 1998) | accessmonthday=June 9 | accessyear=2006}}</ref><ref>{{cite web | url=http://citeseer.ist.psu.edu/cardelli85understanding.html | title=On Understanding Types, Data Abstraction, and Polymorphism | author=[[Luca Cardelli]] and [[Peter Wegner]] | work=Manuscript (1985) | accessmonthday=June 9 | accessyear=2006}}</ref>
===Execution semantics===
Once data has been specified, the machine must be instructed to perform operations on the data. The ''execution semantics'' of a language defines how and when the various constructs of a language should produce a program behavior.
For example, the semantics may define the [[evaluation strategy|strategy]] by which expressions are evaluated to values, or the manner in which [[control structure]]s conditionally execute statements.
===Core library===
{{details|Standard library}}
Most programming languages have an associated [[library (computer science)|core library]] (sometimes known as the 'Standard library', especially if it is included as part of the published language standard), which is conventionally made available by all implementations of the language. Core libraries typically include definitions for commonly used algorithms, data structures, and mechanisms for input and output.
A language's core library is often treated as part of the language by its users, although the designers may have treated it as a separate entity. Many language specifications define a core that must be made available in all implementations, and in the case of standardized languages this core library may be required. The line between a language and its core library therefore differs from language to language. Indeed, some languages are designed so that the meanings of certain syntactic constructs cannot even be described without referring to the core library. For example, in [[Java (programming language)|Java]], a string literal is defined as an instance of the <tt>java.lang.String</tt> class; similarly, in [[Smalltalk]], an [[anonymous function]] expression (a "block") constructs an instance of the library's <tt>BlockContext</tt> class. Conversely, [[Scheme (programming language)|Scheme]] contains multiple coherent subsets that suffice to construct the rest of the language as library macros, and so the language designers do not even bother to say which portions of the language must be implemented as language constructs, and which must be implemented as parts of a library.
==Practice==
A language's designers and users must construct a number of artifacts that govern and enable the practice of programming. The most important of these artifacts are the language ''specification'' and ''implementation''.
===Specification===
{{details|Programming language specification}}
The '''specification''' of a programming language is intended to provide a definition that the language [[programmer|user]]s and the [[programming language implementation|implementors]] can use to determine whether the behavior of a [[computer program|program]] is correct, given its [[source code]].
A programming language specification can take several forms, including the following:
* An explicit definition of the syntax, static semantics, and execution semantics of the language. While syntax is commonly specified using a formal grammar, semantic definitions may be written in [[natural language]] (e.g., the [[C (programming language)|C language]]), or a [[formal semantics of programming languages|formal semantics]] (e.g., the [[Standard ML]]<ref>{{cite book
| last = Milner
| first = R.
| authorlink = Robin Milner
| coauthors = [[Mads Tofte|M. Tofte]], [[Robert Harper (computer scientist)|R. Harper]] and D. MacQueen.
| title = The Definition of Standard ML (Revised)
| publisher = MIT Press
| year = 1997
| id = ISBN 0-262-63181-4 }}</ref> and [[Scheme (programming language)|Scheme]]<ref>{{cite web|first=Richard |last=Kelsey|coauthors=William Clinger and Jonathan Rees|title=Section 7.2 Formal semantics|work=Revised<sup>5</sup> Report on the Algorithmic Language Scheme|url = http://www.schemers.org/Documents/Standards/R5RS/HTML/r5rs-Z-H-10.html#%_sec_7.2| year=1998|month=February|accessdate=2006-06-09}}</ref> specifications).
* A description of the behavior of a [[compiler|translator]] for the language (e.g., the [[C++]] and [[Fortran]] specifications). The syntax and semantics of the language have to be inferred from this description, which may be written in natural or a formal language.
* A ''reference'' or ''model'' implementation, sometimes written in the language being specified (e.g., [[Prolog]] or [[Rexx|ANSI REXX]]<ref>[[ANSI]] — Programming Language Rexx, X3-274.1996</ref>). The syntax and semantics of the language are explicit in the behavior of the reference implementation.
===Implementation===
{{details|Programming language implementation}}
An '''implementation''' of a programming language provides a way to execute that program on one or more configurations of hardware and software. There are, broadly, two approaches to programming language implementation: ''[[compiler|compilation]]'' and ''[[interpreter (computing)|interpretation]]''. It is generally possible to implement a language using either technique.
The output of a [[compiler]] may be executed by hardware or a program called an interpreter. In some implementations that make use of the interpreter approach there is no distinct boundary between compiling and interpreting. For instance, some implementations of the [[BASIC programming language]] compile and then execute the source a line at a time.
Programs that are executed directly on the hardware usually run several orders of magnitude faster than those that are interpreted in software.
One technique for improving the performance of interpreted programs is [[just-in-time compilation]]. Here the [[virtual machine]], just before execution, translates the blocks of [[bytecode]] which are going to be used to machine code, for direct execution on the hardware.
==History==
[[Image:Programming language textbooks.jpg|thumb|230px|right|A selection of textbooks that teach programming, in languages both popular and obscure. These are only a few of the thousands of programming languages and dialects that have been designed in history.]]
{{details|History of programming languages}}
===Early developments===
The first programming languages predate the modern computer. The 19th century had "programmable" [[loom]]s and [[player piano]] scrolls which implemented what are today recognized as examples of [[domain-specific programming language]]s. By the beginning of the twentieth century, punch cards encoded data and directed mechanical processing. In the 1930s and 1940s, the formalisms of [[Alonzo Church]]'s [[lambda calculus]] and [[Alan Turing]]'s [[Turing machine]]s provided mathematical abstractions for expressing [[algorithm]]s; the lambda calculus remains influential in language design.<ref>Benjamin C. Pierce writes:
:"... the lambda calculus has seen widespread use in the specification of programming language features, in language design and implementation, and in the study of type systems."
{{cite book
| last=Pierce
| first=Benjamin C.
| authorlink=Benjamin C. Pierce
| title=Types and Programming Languages
| publisher=[[MIT Press]]
| year=2002
| id=ISBN 0-262-16209-1
| pages=52
}}</ref>
In the 1940s, the first electrically powered digital computers were created. The first [[high-level programming language|high-level]] programming language to be designed for a computer was [[Plankalkül]], developed for the [[Germany|German]] [[Z3 (computer)|Z3]] by [[Konrad Zuse]] between 1943 and 1945.
The computers of the early 1950s, notably the [[UNIVAC I]] and the [[IBM 701]] used [[Machine code|machine language programs]]. [[First-generation programming language|First generation]] machine language programming was quickly superseded by a [[Second-generation programming language|second generation]] of programming languages known as [[Assembly language]]s. Later in the 1950s, assembly language programming, which had evolved to include the use of [[macro instruction]]s, was followed by the development of three higher-level programming languages: [[FORTRAN]], [[Lisp programming language|LISP]], and [[COBOL]]. Updated versions of all of these are still in general use, and importantly, each has strongly influenced the development of later languages.<ref name="influences"> {{cite web
| url=http://www.oreilly.com/news/graphics/prog_lang_poster.pdf
| type=pdf
| title=History of programming languages
| author=[[O'Reilly Media]]
| accessmonthday=October 5
| accessyear=2006
}}</ref> At the end of the 1950s, the language formalized as [[Algol 60]] was introduced, and most later programming languages are, in many respects, descendants of Algol.<ref name="influences"/> The format and use of the early programming languages was heavily influenced by the [[Computer programming in the punch card era|constraints of the interface]].<ref>Frank da Cruz. [http://www.columbia.edu/acis/history/cards.html IBM Punch Cards] [http://www.columbia.edu/acis/history/index.html Columbia University Computing History].</ref>
===Refinement===
The period from the 1960s to the late 1970s brought the development of the major language paradigms now in use, though many aspects were refinements of ideas in the very first [[Third-generation programming language]]s:
*[[APL (programming language)|APL]] introduced ''[[array programming]]'' and influenced [[functional programming]].<ref>Richard L. Wexelblat: ''History of Programming Languages'', Academic Press, 1981, chapter XIV.</ref>
*[[PL/I]] (NPL) was designed in the early 1960s to incorporate the best ideas from FORTRAN and COBOL.
*In the 1960s, [[Simula programming language|Simula]] was the first language designed to support ''[[object-oriented programming]]''; in the mid-1970s, [[Smalltalk programming language|Smalltalk]] followed with the first "purely" object-oriented language.
*[[C (programming language)|C]] was developed between 1969 and 1973 as a ''[[systems programming]]'' language, and remains popular.<ref>{{cite web | url=http://www.cs.berkeley.edu/~flab/languages.html | author=François Labelle | title=Programming Language Usage Graph | work=[[Sourceforge]] | accessmonthday=June 21 | accessyear=2006}}. This comparison analyzes trends in number of projects hosted by a popular community programming repository. During most years of the comparison, C leads by a considerable margin; in 2006, Java overtakes C, but the combination of C/C++ still leads considerably.</ref>
*[[Prolog programming language|Prolog]], designed in 1972, was the first ''[[logic programming]]'' language.
*In 1978, [[ML programming language|ML]] built a polymorphic type system on top of Lisp, pioneering ''[[static typing|statically typed]] [[functional programming]]'' languages.
Each of these languages spawned an entire family of descendants, and most modern languages count at least one of them in their ancestry.
The 1960s and 1970s also saw considerable debate over the merits of ''[[structured programming]]'', and whether programming languages should be designed to support it.<ref> {{Citation | title=The Semicolon Wars | journal=American Scientist | first1=Brian | last1=Hayes | volume=94 | issue=4 | year=2006 | pages=pp. 299–303}} </ref> [[Edsger W. Dijkstra|Edsger Dijkstra]], in a famous 1968 letter published in the [[Communications of the ACM]], argued that [[GOTO]] statements should be eliminated from all "higher level" programming languages.<ref>{{cite journal|last=Dijkstra|first=Edsger W.|authorlink=Edsger Dijkstra|title=Go To Statement Considered Harmful|journal=Communications of the ACM|volume=11|issue=3|month=March|year=1968|pages=147–148|url=http://www.acm.org/classics/oct95/|accessdate=2006-06-29|doi=10.1145/362929.362947}}</ref>
The 1960s and 1970s also saw expansion of techniques that reduced the footprint of a program as well as improved productivity of the programmer and user. The [[Computer programming in the punch card era|card deck]] for an early [[Fourth-generation programming language|4GL]] was a lot smaller for the same functionality expressed in a [[Third-generation programming language|3GL deck]].
===Consolidation and growth===
The 1980s were years of relative consolidation. [[C Plus Plus|C++]] combined object-oriented and systems programming. The United States government standardized [[Ada programming language|Ada]], a systems programming language intended for use by defense contractors. In Japan and elsewhere, vast sums were spent investigating so-called [[Fifth generation computer|"fifth generation" languages]] that incorporated logic programming constructs.<ref>
Tetsuro Fujise, Takashi Chikayama
Kazuaki Rokusawa, Akihiko Nakase (December 1994). "KLIC: A Portable Implementation of KL1" ''Proc. of FGCS '94, ICOT'' Tokyo, December 1994. [http://www.icot.or.jp/ARCHIVE/HomePage-E.html KLIC is a portable implementation of a concurrent logic programming language [[KL1]].]</ref> The functional languages community moved to standardize ML and Lisp. Rather than inventing new paradigms, all of these movements elaborated upon the ideas invented in the previous decade.
One important trend in language design during the 1980s was an increased focus on programming for large-scale systems through the use of ''modules'', or large-scale organizational units of code. [[Modula-2]], Ada, and ML all developed notable module systems in the 1980s, although other languages, such as [[PL/I]], already had extensive support for modular programming. Module systems were often wedded to [[generic programming]] constructs.<ref>{{cite web|author=Jim Bender|url=http://readscheme.org/modules/|title=Mini-Bibliography on Modules for Functional Programming Languages|work=ReadScheme.org|accessdate=2006-09-27|date=March 15th, 2004}}</ref>
The rapid growth of the [[Internet]] in the mid-1990's created opportunities for new languages. [[Perl]], originally a Unix scripting tool first released in 1987, became common in dynamic [[Web site]]s. [[Java (programming language)|Java]] came to be used for server-side programming. These developments were not fundamentally novel, rather they were refinements to existing languages and paradigms, and largely based on the C family of programming languages.
Programming language evolution continues, in both industry and research. Current directions include security and reliability verification, new kinds of modularity ([[mixin]]s, [[Delegation (programming)|delegates]], [[aspect-oriented programming|aspects]]), and database integration. {{Fact|date=February 2007}}
The [[4GL]]s are examples of languages which are domain-specific, such as [[SQL]], which manipulates and returns [[set]]s of data rather than the scalar values which are canonical to most programming languages. [[Perl]], for example, with its '[[here document]]' can hold multiple 4GL programs, as well as multiple JavaScript programs, in part of its own perl code and use variable interpolation in the 'here document' to support multi-language programming.<ref>Wall, ''Programming Perl'' ISBN 0-596-00027-8 p.66</ref>
=== Measuring language usage ===
It is difficult to determine which programming languages are most widely used, and what usage means varies by context. One language may occupy the greater number of programmer hours, a different one have more lines of code, and a third utilize the most CPU time. Some languages are very popular for particular kinds of applications. For example, [[COBOL]] is still strong in the corporate data center, often on large [[Mainframe computer|mainframes]]; [[Fortran (programming language)|FORTRAN]] in engineering applications; [[C (programming language)|C]] in embedded applications and operating systems; and other languages are regularly used to write many different kinds of applications.
Various methods of measuring language popularity, each subject to a different bias over what is measured, have been proposed:
*counting the number of job advertisements that mention the language<ref>[http://www.computerweekly.com/Articles/2007/09/11/226631/sslcomputer-weekly-it-salary-survey-finance-boom-drives-it-job.htm Survey of Job advertisements mentioning a given language]</ref>
*the number of books sold that teach or describe the language<ref>[http://radar.oreilly.com/archives/2006/08/programming_language_trends_1.html Counting programming languages by book sales]</ref>
*estimates of the number of existing lines of code written in the language—which may underestimate languages not often found in public searches<ref>Bieman, J.M.; Murdock, V., Finding code on the World Wide Web: a preliminary investigation, Proceedings First IEEE International Workshop on Source Code Analysis and Manipulation, 2001</ref>
*counts of language references found using a web search engine.
==Taxonomies==
{{details|Categorical list of programming languages}}
There is no overarching classification scheme for programming languages. A given programming language does not usually have a single ancestor language. Languages commonly arise by combining the elements of several predecessor languages with new ideas in circulation at the time. Ideas that originate in one language will diffuse throughout a family of related languages, and then leap suddenly across familial gaps to appear in an entirely different family.
The task is further complicated by the fact that languages can be classified along multiple axes. For example, Java is both an object-oriented language (because it encourages object-oriented organization) and a concurrent language (because it contains built-in constructs for running multiple [[Thread (computer science)|threads]] in parallel). [[Python (programming language)|Python]] is an object-oriented [[scripting language]].
In broad strokes, programming languages divide into ''[[programming paradigm]]s'' and a classification by ''intended domain of use''. Paradigms include [[procedural programming]], [[object-oriented programming]], [[functional programming]], and [[logic programming]]; some languages are hybrids of paradigms or multi-paradigmatic. An [[assembly language]] is not so much a paradigm as a direct model of an underlying machine architecture. By purpose, programming languages might be considered general purpose, system programming languages, scripting languages, domain-specific languages, or concurrent/distributed languages (or a combination of these).<ref>{{cite web|url=http://tunes.org/wiki/programming_20languages.html|title=TUNES: Programming Languages}}</ref> Some general purpose languages were designed largely with educational goals.<ref>{{cite journal|last=Wirth|first=Niklaus|authorlink=Niklaus Wirth|title=Recollections about the development of Pascal|journal=Proc. 2nd [[ACM SIGPLAN]] conference on history of programming languages|pages=333–342|year=1993|url=http://portal.acm.org/citation.cfm?id=155378|accessdate=2006-06-30|doi=10.1145/154766.155378}}</ref>
A programming language may also be classified by factors unrelated to programming paradigm. For instance, most programming languages use [[English language]] keywords, while a [[Categorical list of programming languages#Non-English-based languages|minority do not]]. Other languages may be classified as being [[Esoteric programming language|esoteric]] or not.
==See also==
{{portal|Computer science}}
{{wikibooks|Computer programming}}
{{wiktionarypar|programming language}}
*[[Lists of programming languages]]
*[[Comparison of programming languages]]
*[[Comparison of basic instructions of programming languages]]
*[[Educational programming language]]
*[[Invariant based programming]]
*[[Literate programming]]
*[[Programming language dialect]]
*[[Programming language theory]]
*[[Computer science]] and [[List of basic computer science topics]]
*[[Software engineering]] and [[List of software engineering topics]]
==References==
{{Reflist}}
==Further reading==
*Daniel P. Friedman, Mitchell Wand, Christopher Thomas Haynes: ''Essentials of Programming Languages'', The MIT Press 2001.
*David Gelernter, Suresh Jagannathan: ''Programming Linguistics'', The MIT Press 1990.
*Shriram Krishnamurthi: ''Programming Languages: Application and Interpretation'', [http://www.cs.brown.edu/~sk/Publications/Books/ProgLangs/ online publication].
*Bruce J. MacLennan: ''Principles of Programming Languages: Design, Evaluation, and Implementation'', Oxford University Press 1999.
*John C. Mitchell: ''Concepts in Programming Languages'', Cambridge University Press 2002.
*Benjamin C. Pierce: ''Types and Programming Languages'', The MIT Press 2002.
*Ravi Sethi: ''Programming Languages: Concepts and Constructs'', 2nd ed., Addison-Wesley 1996.
*Michael L. Scott: ''Programming Language Pragmatics'', Morgan Kaufmann Publishers 2005.
*Richard L. Wexelblat (ed.): ''History of Programming Languages'', Academic Press 1981.
==External links==
*[http://www.99-bottles-of-beer.net/ 99 Bottles of Beer] A collection of implementations in many languages.
*[http://www.levenez.com/lang/history.html Computer Languages History graphical chart]
*[http://cgibin.erols.com/ziring/cgi-bin/cep/cep.pl Dictionary of Programming Languages]
*[http://hopl.murdoch.edu.au/ History of Programming Languages (HOPL)]
*[http://dmoz.org/Computers/Programming/Languages/ Open Directory - Computer Programming Languages]
*[http://merd.sourceforge.net/pixel/language-study/syntax-across-languages/ Syntax Patterns for Various Languages]
*[http://www.ulb.ac.be/di/rwuyts/INFO020_2003/grogono-evolution.pdf The Evolution of Programming Languages] by Peter Grogono
*[http://lambda-the-ultimate.org/policies#Purpose Lambda the Ultimate], a community weblog for professional discussion and repository of documents on [[programming language theory]].
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