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A programming language is a machine-readable artificial language designed to
express computations that can be performed by a machine, particularly a
computer. Programming languages can be used to create programs that specify
the behavior of a machine, to express algorithms precisely, or as a mode of
human communication.

Many programming languages have some form of written specification of their
syntax and semantics, since computers require precisely defined instructions.
Some are defined by a specification document (for example, an ISO Standard),
while others have a dominant implementation (such as Perl).

The earliest programming languages predate the invention of the computer, and
were used to direct the behavior of machines such as automated looms and
player pianos. Thousands of different programming languages have been
created, mainly in the computer field [1], where many more are being created
every year.


- Definitions -

Traits often considered important for constituting a programming language:

    * Function: A programming language is a language used to write computer
programs, which involve a computer performing some kind of computation[2] or
algorithm and possibly control external devices such as printers, robots,[3]
and so on.

    * Target: Programming languages differ from natural languages 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 structures or controlling the 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 algorithms. ANSI/ISO SQL and Charity are
examples of languages that are not Turing complete, yet often called
programming languages.[4][5]

Some authors restrict the term "programming language" to those languages that
can express all possible algorithms;[6] sometimes the term "computer
language" is used for more limited artificial languages.

Non-computational languages, such as markup languages like HTML or formal
grammars like 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.

- Usage -

A programming language provides a structured mechanism for defining pieces of
data, and the operations or transformations that may be carried out
automatically on that data. A programmer uses the abstractions present in the
language to represent the concepts involved in a computation. These concepts
are represented as a collection of the simplest elements available (called
primitives). [7]

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, a
program, and the program's inputs must fully specify the external behavior
that occurs when the program is executed, within the domain of control of
that program.

Programs for a computer might be executed in a batch process without human
interaction, or a user might type commands in an interactive session of an
interpreter. In this case the "commands" are simply programs, whose execution
is chained together. When a language is used to give commands to a software
application (such as a shell) it is called a scripting language.

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 generally accepted as
filling this role.[8] 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 microcontrollers to supercomputers.
    * 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. 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.[9]

Natural language processors 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."[10] Alan Perlis was similarly dismissive of the
idea.[11]

- Elements -

All programming languages have some primitive building blocks for the
description of data and the processes or transformations applied to them
(like the addition of two numbers or the selection of an item from a
collection). These primitives are defined by syntactic and semantic rules
which describe their structure and meaning respectively.

Syntax

    For more details on this topic, see Syntax (programming languages).

A programming language's surface form is known as its 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 graphical in nature, using visual 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 or hard-coded in a reference
implementation). Since most languages are textual, this article discusses
textual syntax.

Programming language syntax is usually defined using a combination of regular
expressions (for lexical structure) and Backus-Naur Form (for grammatical
structure). Below is a simple grammar, based on Lisp:

expression ::= atom | list
atom  ::= number | symbol
number  ::= [+-]?['0'-'9']+
symbol  ::= ['A'-'Z''a'-'z'].*
list  ::= '(' expression* ')'

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:
'12345', '()', '(a b c232 (1))'

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 p is a null pointer, the
operations p->real and p->im 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
grammars.[12]

Static semantics

The static semantics defines restrictions on the structure of valid texts
that are hard or impossible to express in standard syntactic formalisms.[13]
The most important of these restrictions are covered by type systems.

Type system

    For more details on this topic, see Type system.
    For more details on this topic, see 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 structures that
can be constructed in the language. The design and study of type systems
using formal mathematics is known as type theory.

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.[14] For example, "this text between the
quotes" 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.

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 languages, allows any
operation to be performed on any data, which are generally considered to be
sequences of bits of various lengths.[14] High-level languages which are
untyped include BCPL and some varieties of 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.[14] 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.[14]

Statically-typed languages can be either manifestly typed or type-inferred.
In the first case, the programmer must explicitly write types at certain
textual positions (for example, at variable declarations). In the second
case, the compiler infers the types of expressions and declarations based on
context. Most mainstream statically-typed languages, such as C++, C# and
Java, are manifestly typed. Complete type inference has traditionally been
associated with less mainstream languages, such as Haskell and ML. However,
many manifestly typed languages support partial type inference; for example,
Java and C# both infer types in certain limited cases.[15]

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.[14] 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, Lisp, JavaScript, and 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.[14] 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.[14] Strongly-typed languages are often
termed type-safe or 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 2 * x implicitly
converts x to a number, and this conversion succeeds even if x is null,
undefined, an Array, 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 has been called both strongly typed and weakly, statically
typed.[16][17]

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 strategy by which expressions are
evaluated to values, or the manner in which control structures conditionally
execute statements.

Core library

    For more details on this topic, see Standard library.

Most programming languages have an associated 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, a string literal
is defined as an instance of the java.lang.String class; similarly, in
Smalltalk, an anonymous function expression (a "block") constructs an
instance of the library's BlockContext class. Conversely, 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

    For more details on this topic, see Programming language specification.

The specification of a programming language is intended to provide a
definition that the language users and the implementors can use to determine
whether the behavior of a 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
language), or a formal semantics (e.g., the Standard ML[18] and Scheme[19]
specifications).
    * A description of the behavior of a 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 ANSI REXX[20]). The syntax and semantics of
the language are explicit in the behavior of the reference implementation.


Implementation

    For more details on this topic, see 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: compilation
and 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.[citation needed]

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 -

    For more details on this topic, see History of programming languages.


Early developments

The first programming languages predate the modern computer. The 19th century
had "programmable" looms and player piano scrolls which implemented what are
today recognized as examples of domain-specific programming languages. 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 machines provided
mathematical abstractions for expressing algorithms; the lambda calculus
remains influential in language design.[21]

In the 1940s, the first electrically powered digital computers were created.
The first high-level programming language to be designed for a computer was
Plankalkül, developed for the German Z3 by Konrad Zuse between 1943 and 1945.

Programmers of early 1950s computers, notably UNIVAC I and IBM 701, used
machine language programs, that is, the first generation language (1GL). 1GL
programming was quickly superseded by similarly machine-specific, but
mnemonic, second generation languages (2GL) known as Assembly languages or
"assembler". Later in the 1950s, assembly language programming, which had
evolved to include the use of macro instructions, was followed by the
development of "third generation" programming languages (3GL), such as
FORTRAN, LISP, and COBOL. 3GLs are more abstract and are "portable", or at
least implemented similar on computers that do not support the same native
machine code. Updated versions of all of these 3GLs are still in general use,
and each has strongly influenced the development of later languages.[22] 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.[22] The format and use of the early programming languages was heavily
influenced by the constraints of the interface.[23]

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 languages:

    * APL introduced array programming and influenced functional
programming.[24]
    * PL/I (NPL) was designed in the early 1960s to incorporate the best
ideas from FORTRAN and COBOL.
    * In the 1960s, Simula was the first language designed to support
object-oriented programming; in the mid-1970s, Smalltalk followed with the
first "purely" object-oriented language.
    * C was developed between 1969 and 1973 as a systems programming
language, and remains popular.[25]
    * Prolog, designed in 1972, was the first logic programming language.
    * In 1978, ML built a polymorphic type system on top of Lisp, pioneering
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.[26] 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.[27]

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 card deck for an early 4GL was a lot smaller for the same
functionality expressed in a 3GL deck.

Consolidation and growth

The 1980s were years of relative consolidation. C++ combined object-oriented
and systems programming. The United States government standardized Ada, a
systems programming language intended for use by defense contractors. In
Japan and elsewhere, vast sums were spent investigating so-called "fifth
generation" languages that incorporated logic programming constructs.[28] 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.[29]

The rapid growth of the Internet in the mid-1990s created opportunities for
new languages. Perl, originally a Unix scripting tool first released in 1987,
became common in dynamic Web sites. 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 (mixins, delegates, aspects), and database
integration.[citation needed]

The 4GLs are examples of languages which are domain-specific, such as SQL,
which manipulates and returns sets 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.[30]

Measuring language usage

    Main article: Measuring programming language popularity

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 mainframes; FORTRAN in engineering
applications; 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[31]
    * the number of books sold that teach or describe the language[32]
    * estimates of the number of existing lines of code written in the
language—which may underestimate languages not often found in public
searches[33]
    * counts of language references (i.e., to the name of the language) found
using a web search engine.

Combining and averaging information from various internet sites
langpop.com,[34] in 2008 the 10 most cited programming languages are (in
alphabetical order): C, C++, C#, Java, JavaScript, Perl, PHP, Python, Ruby,
and SQL.

- Taxonomies -

    For more details on this topic, see 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
threads in parallel). Python is an object-oriented scripting language.

In broad strokes, programming languages divide into programming paradigms 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).[35] Some general purpose languages were designed
largely with educational goals.[36]

A programming language may also be classified by factors unrelated to
programming paradigm. For instance, most programming languages use English
language keywords, while a minority do not. Other languages may be classified
as being esoteric or not.

http://en.wikipedia.org/wiki/Programming_language