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A programming language is an artificial language that can be used to Control#Science and Technology the behavior of a machine, particularly a computer. Programming languages, like natural languagess, are defined by syntax and semantic rules which describe their structure and meaning respectively. Programming languages often (but not always) formally specify syntax and semantics to make them easier to parse and interpret.

Programming languages are used to facilitate communication about the task of organizing and manipulating information, and to express algorithms precisely. Some authors restrict the term "programming language" to those languages that can express all possible algorithms;In mathematical terms, this means the programming language is Turing-complete sometimes the term "computer language" is used for more limited artificial languages.

Alphabetical list of programming languagesas of 2006 The Encyclopedia of Computer Languages by Murdoch University, Australia lists 8512 computer languages. have been created, and new languages are created every year.

Definitions Traits often considered important for constituting a programming language:









Non-computational languages, such as markup languages like HTML or formal grammars like Backus–Naur form, are usually not considered programming languages. Often a programming language is embedded in the non-computational (host) language.

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, computers do exactly what they are told to do, and cannot understand the code the programmer "intended" to write. The combination of the language definition, the computer 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.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. (). Ada programming language and UNCOL had similar early goals. The need for diverse computer languages arises from the diversity of contexts in which languages are used:



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). 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 removed from simple translation into underlying hardware instructions. Because programmers are less tied to the needs of the computer, their programs can do more computing with less effort from the programmer. This lets them write more programs in the same amount of time. Frederick P. Brooks, Jr.: The Mythical Man-Month, Addison-Wesley, 1982, pp. 93-94

Natural language and computations 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."Dijkstra, Edsger W. On the foolishness of "natural language programming." EWD667. Alan Perlis was similarly dismissive of the idea.Perlis, Alan, Epigrams on Programming. SIGPLAN Notices Vol. 17, No. 9, September 1982, pp. 7-13

Elements Syntax of Python code with inset tokenization is often used to aid programmers in the recognition of elements of source code. The language you see here is Python (programming language)

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 visual programming language 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. Since most languages are textual, this article discusses textual syntax.

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

expression ::= atom | listatom ::= number | symbolnumber ::= ?+symbol ::= .*list ::= '(' expression* ')'

This grammar specifies the following:

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:

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. Section 2.2: Pushdown Automata, pp.101–114.

Type system 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.

Internally, all data in modern digital computers are stored simply as zeros or ones (Binary numeral system). The data typically represent information in the real world such as names, bank accounts and measurements, so the low-level binary data are organized by programming languages into these high-level concepts as data types. There are also more abstract types whose purpose is just to warn the programmer about semantically meaningless statements or verify safety properties of programs.

Most languages can be classified with respect to their type systems, though some such as Visual Basic allow the programmer to choose the system employed.

Typed vs untyped languages A language is typed if operations defined for one data type cannot be performed on values of another data type. 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 handling.

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. High-level languages which are untyped include BCPL and some varieties of Forth (programming language).

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. Many production languages provide means to bypass or subvert the type system.

Static vs 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.

Statically-typed languages can be manifestly typed or type inference. In the first case, the programmer must explicitly write types at certain textual positions (for example, at variable declaration (computer science)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 and Java (programming language), are manifestly typed. Complete type inference has traditionally been associated with less mainstream languages, such as Haskell (programming language) and ML programming language. However, many manifestly typed languages support partial type inference; for example, Java (programming language) and C Sharp both infer types in certain limited cases.Specifically, instantiations of generic programming 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: Generic Java type inference is unsound (Alan Jeffrey, 17 Dec 2001) and Sound Generic Java type inference (Martin Odersky, 15 Jan 2002). C#'s type system is similar to Java's, and uses a similar partial type inference scheme.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. 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), Lisp programming language, JavaScript, and Python (programming language) 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. This can occasionally be useful, but it can also allow some kinds of program faults to go undetected at compile time.

Strong typing prevents the above. Attempting to mix types raises an error. Strongly-typed languages are often termed type-safe or type safety. Type safety can prevent particular kinds of program faults occurring (because constructs containing them are flagged at compile time).

An alternative definition for "weakly typed" refers to languages, such as Perl, JavaScript, and C++ which permit a large number of implicit type conversions; Perl in particular can be characterized as a dynamically typed programming language in which type checking can take place at runtime. See type system. This capability is often useful, but occasionally dangerous; as it would permit operations whose objects can change type on demand.

Strong and static are 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) has been called both strongly typed and weakly, statically typed..

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

Core library Most programming languages have an associated library (computer science) (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), 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 (programming language) 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 The specification of a programming language is intended to provide a definition that language programmers and programming language implementation can use to determine the behavior of a computer program, given its source code.

A programming language specification can take several forms, including the following:

| last = Milner | first = R. | authorlink = Robin Milner | coauthors = [Mads Tofte, [Robert Harper (computer scientist) and D. MacQueen. | title = The Definition of Standard ML (Revised) | publisher = MIT Press | year = 1997 | id = ISBN 0-262-63181-4 -->and [Scheme (programming language){{cite web|first=Richard |last=Kelsey|coauthors=William Clinger and Jonathan Rees|title=Section 7.2 Formal semantics|work=Revised5 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--> specifications).

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 and interpreter (computing). 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 monitors which sequences of bytecode are frequently executed and translates them to machine code for direct execution on the hardware.

History

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.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 -->

In the 1940s, the first electrically powered digital computers were created. The computers of the early 1950s, notably the UNIVAC I and the IBM 701 used Machine code. First-generation programming language machine language programming was quickly superseded by a Second-generation programming language of programming languages known as Assembly languages. Later in the 1950s, assembly language programming, which had evolved to include the use of macro instructions, was followed by the development of three higher-level programming languages: FORTRAN, Lisp programming language, and COBOL. Updated versions of all of these are still in general use, and importantly, each has strongly influenced the development of later languages. {{cite web| url=http://www.oreilly.com/news/graphics/prog_lang_poster.pdf | type=pdf | title=History of programming languages | author=[O'Reilly Media | accessdate=October 5 | accessyear=2006 --> 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. The format and use of the early programming languages was heavily influenced by the Computer programming in the punch card era.Frank da Cruz. IBM Punch Cards Columbia University Computing History.

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: 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. Edsger W. 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.

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 for an early Fourth-generation programming language was a lot smaller for the same functionality expressed in a Third-generation programming language.

Consolidation and growth The 1980s were years of relative consolidation. C Plus Plus combined object-oriented and systems programming. The United States government standardized Ada programming language, a systems programming language intended for use by defense contractors. In Japan and elsewhere, vast sums were spent investigating so-called Fifth generation computer that incorporated logic programming constructsTetsuro Fujise, Takashi ChikayamaKazuaki Rokusawa, Akihiko Nakase (December 1994). "KLIC: A Portable Implementation of KL1" Proc. of FGCS '94, ICOT Tokyo, December 1994. KLIC is a portable implementation of a concurrent logic programming language KL1.]. 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.

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 sites. Java (programming language) 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, Delegation (programming), aspect-oriented programming), and database integration.

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 programmingWall, Programming Perl ISBN 0-596-00027-8 p.66.

Measuring language usage It is difficult to determine which programming languages are most used. Some languages are very popular for particular kinds of applications (e.g., COBOL is still strong in the corporate data center, often on large Mainframe computer, Fortran (programming language) in engineering applications, and C (programming language) in embedded applications and operating systems), while some languages are regularly used to write many different kinds of applications.

Methods of measuring language popularity include counting the number of job advertisements that mention the language; Survey of Job advertisements mentioning a given language the number of books sold that teach or describe the language sold; estimates of the number of existing lines of code written in the language; counts of language references found using a web search engine. Each measurement methodology is subject to a different skew in what it measures.

Taxonomies 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) in parallel). Python (programming language) 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). Some general purpose languages were designed largely with educational goals.

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. Other languages may be classified as being Esoteric programming language or not.

See also

References Further reading

External links

A programming language is an artificial language that can be used to Control#Science and Technology the behavior of a machine, particularly a computer. Programming languages, like natural languagess, are defined by syntax and semantic rules which describe their structure and meaning respectively. Programming languages often (but not always) formally specify syntax and semantics to make them easier to parse and interpret.

Programming languages are used to facilitate communication about the task of organizing and manipulating information, and to express algorithms precisely. Some authors restrict the term "programming language" to those languages that can express all possible algorithms;In mathematical terms, this means the programming language is Turing-complete sometimes the term "computer language" is used for more limited artificial languages.

Alphabetical list of programming languagesas of 2006 The Encyclopedia of Computer Languages by Murdoch University, Australia lists 8512 computer languages. have been created, and new languages are created every year.

Definitions Traits often considered important for constituting a programming language:









Non-computational languages, such as markup languages like HTML or formal grammars like Backus–Naur form, are usually not considered programming languages. Often a programming language is embedded in the non-computational (host) language.

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, computers do exactly what they are told to do, and cannot understand the code the programmer "intended" to write. The combination of the language definition, the computer 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.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. (). Ada programming language and UNCOL had similar early goals. The need for diverse computer languages arises from the diversity of contexts in which languages are used:



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). 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 removed from simple translation into underlying hardware instructions. Because programmers are less tied to the needs of the computer, their programs can do more computing with less effort from the programmer. This lets them write more programs in the same amount of time. Frederick P. Brooks, Jr.: The Mythical Man-Month, Addison-Wesley, 1982, pp. 93-94

Natural language and computations 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."Dijkstra, Edsger W. On the foolishness of "natural language programming." EWD667. Alan Perlis was similarly dismissive of the idea.Perlis, Alan, Epigrams on Programming. SIGPLAN Notices Vol. 17, No. 9, September 1982, pp. 7-13

Elements Syntax of Python code with inset tokenization is often used to aid programmers in the recognition of elements of source code. The language you see here is Python (programming language)

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 visual programming language 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. Since most languages are textual, this article discusses textual syntax.

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

expression ::= atom | listatom ::= number | symbolnumber ::= ?+symbol ::= .*list ::= '(' expression* ')'

This grammar specifies the following:

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:

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. Section 2.2: Pushdown Automata, pp.101–114.

Type system 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.

Internally, all data in modern digital computers are stored simply as zeros or ones (Binary numeral system). The data typically represent information in the real world such as names, bank accounts and measurements, so the low-level binary data are organized by programming languages into these high-level concepts as data types. There are also more abstract types whose purpose is just to warn the programmer about semantically meaningless statements or verify safety properties of programs.

Most languages can be classified with respect to their type systems, though some such as Visual Basic allow the programmer to choose the system employed.

Typed vs untyped languages A language is typed if operations defined for one data type cannot be performed on values of another data type. 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 handling.

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. High-level languages which are untyped include BCPL and some varieties of Forth (programming language).

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. Many production languages provide means to bypass or subvert the type system.

Static vs 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.

Statically-typed languages can be manifestly typed or type inference. In the first case, the programmer must explicitly write types at certain textual positions (for example, at variable declaration (computer science)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 and Java (programming language), are manifestly typed. Complete type inference has traditionally been associated with less mainstream languages, such as Haskell (programming language) and ML programming language. However, many manifestly typed languages support partial type inference; for example, Java (programming language) and C Sharp both infer types in certain limited cases.Specifically, instantiations of generic programming 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: Generic Java type inference is unsound (Alan Jeffrey, 17 Dec 2001) and Sound Generic Java type inference (Martin Odersky, 15 Jan 2002). C#'s type system is similar to Java's, and uses a similar partial type inference scheme.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. 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), Lisp programming language, JavaScript, and Python (programming language) 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. This can occasionally be useful, but it can also allow some kinds of program faults to go undetected at compile time.

Strong typing prevents the above. Attempting to mix types raises an error. Strongly-typed languages are often termed type-safe or type safety. Type safety can prevent particular kinds of program faults occurring (because constructs containing them are flagged at compile time).

An alternative definition for "weakly typed" refers to languages, such as Perl, JavaScript, and C++ which permit a large number of implicit type conversions; Perl in particular can be characterized as a dynamically typed programming language in which type checking can take place at runtime. See type system. This capability is often useful, but occasionally dangerous; as it would permit operations whose objects can change type on demand.

Strong and static are 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) has been called both strongly typed and weakly, statically typed..

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

Core library Most programming languages have an associated library (computer science) (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), 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 (programming language) 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 The specification of a programming language is intended to provide a definition that language programmers and programming language implementation can use to determine the behavior of a computer program, given its source code.

A programming language specification can take several forms, including the following:

| last = Milner | first = R. | authorlink = Robin Milner | coauthors = [Mads Tofte, [Robert Harper (computer scientist) and D. MacQueen. | title = The Definition of Standard ML (Revised) | publisher = MIT Press | year = 1997 | id = ISBN 0-262-63181-4 -->and [Scheme (programming language){{cite web|first=Richard |last=Kelsey|coauthors=William Clinger and Jonathan Rees|title=Section 7.2 Formal semantics|work=Revised5 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--> specifications).

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 and interpreter (computing). 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 monitors which sequences of bytecode are frequently executed and translates them to machine code for direct execution on the hardware.

History

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.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 -->

In the 1940s, the first electrically powered digital computers were created. The computers of the early 1950s, notably the UNIVAC I and the IBM 701 used Machine code. First-generation programming language machine language programming was quickly superseded by a Second-generation programming language of programming languages known as Assembly languages. Later in the 1950s, assembly language programming, which had evolved to include the use of macro instructions, was followed by the development of three higher-level programming languages: FORTRAN, Lisp programming language, and COBOL. Updated versions of all of these are still in general use, and importantly, each has strongly influenced the development of later languages. {{cite web| url=http://www.oreilly.com/news/graphics/prog_lang_poster.pdf | type=pdf | title=History of programming languages | author=[O'Reilly Media | accessdate=October 5 | accessyear=2006 --> 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. The format and use of the early programming languages was heavily influenced by the Computer programming in the punch card era.Frank da Cruz. IBM Punch Cards Columbia University Computing History.

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: 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. Edsger W. 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.

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 for an early Fourth-generation programming language was a lot smaller for the same functionality expressed in a Third-generation programming language.

Consolidation and growth The 1980s were years of relative consolidation. C Plus Plus combined object-oriented and systems programming. The United States government standardized Ada programming language, a systems programming language intended for use by defense contractors. In Japan and elsewhere, vast sums were spent investigating so-called Fifth generation computer that incorporated logic programming constructsTetsuro Fujise, Takashi ChikayamaKazuaki Rokusawa, Akihiko Nakase (December 1994). "KLIC: A Portable Implementation of KL1" Proc. of FGCS '94, ICOT Tokyo, December 1994. KLIC is a portable implementation of a concurrent logic programming language KL1.]. 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.

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 sites. Java (programming language) 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, Delegation (programming), aspect-oriented programming), and database integration.

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 programmingWall, Programming Perl ISBN 0-596-00027-8 p.66.

Measuring language usage It is difficult to determine which programming languages are most used. Some languages are very popular for particular kinds of applications (e.g., COBOL is still strong in the corporate data center, often on large Mainframe computer, Fortran (programming language) in engineering applications, and C (programming language) in embedded applications and operating systems), while some languages are regularly used to write many different kinds of applications.

Methods of measuring language popularity include counting the number of job advertisements that mention the language; Survey of Job advertisements mentioning a given language the number of books sold that teach or describe the language sold; estimates of the number of existing lines of code written in the language; counts of language references found using a web search engine. Each measurement methodology is subject to a different skew in what it measures.

Taxonomies 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) in parallel). Python (programming language) 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). Some general purpose languages were designed largely with educational goals.

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. Other languages may be classified as being Esoteric programming language or not.

See also

References Further reading

External links



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