A programming language is an 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 control 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 (form) and semantics (meaning). Some languages are defined by a specification document. For example, the C programming language is specified by an ISO Standard. Other languages, such as Perl, have a dominant implementation that is used as a reference.
The earliest programming languages predate the invention of the computer, and were used to direct the behavior of machines such as Jacquard looms and player pianos. Thousands of different programming languages have been created, mainly in the computer field, with many more being created every year. Most programming languages describe computation in an imperative style, i.e., as a sequence of commands, although some languages, such as those that support functional programming or logic programming, use alternative forms of description.
Definitions
A programming language is a notation for writing programs, which are specifications of a computation or algorithm.[1] Some, but not all, authors restrict the term "programming language" to those languages that can express all possible algorithms.[1][2] Traits often considered important for what constitutes a programming language include:
• Function and target: A computer programming language is a language[3] used to write computer programs, which involve a computer performing some kind of computation[4] or algorithm and possibly control external devices such as printers, disk drives, robots,[5] and so on. For example PostScript programs are frequently created by another program to control a computer printer or display. More generally, a programming language may describe computation on some, possibly abstract, machine. It is generally accepted that a complete specification for a programming language includes a description, possibly idealized, of a machine or processor for that language.[6] In most practical contexts, a programming language involves a computer; consequently programming languages are usually defined and studied this way.[7] 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.
• Abstractions: Programming languages usually contain abstractions for defining and manipulating data structures or controlling the flow of execution. The practical necessity that a programming language support adequate abstractions is expressed by the abstraction principle;[8] this principle is sometimes formulated as recommendation to the programmer to make proper use of such abstractions.[9]
• 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.[10][11]
Markup languages like XML, HTML or troff, which define structured data, are not generally considered programming languages.[12][13][14] Programming languages may, however, share the syntax with markup languages if a computational semantics is defined. XSLT, for example, is a Turing complete XML dialect.[15][16][17] Moreover, LaTeX, which is mostly used for structuring documents, also contains a Turing complete subset.[18][19]
The term computer language is sometimes used interchangeably with programming language.[20] However, the usage of both terms varies among authors, including the exact scope of each. One usage describes programming languages as a subset of computer languages.[21] In this vein, languages used in computing that have a different goal than expressing computer programs are generically designated computer languages. For instance, markup languages are sometimes referred to as computer languages to emphasize that they are not meant to be used for programming.[22] Another usage regards programming languages as theoretical constructs for programming abstract machines, and computer languages as the subset thereof that runs on physical computers, which have finite hardware resources.[23] John C. Reynolds emphasizes that formal specification languages are just as much programming languages as are the languages intended for execution. He also argues that textual and even graphical input formats that affect the behavior of a computer are programming languages, despite the fact they are commonly not Turing-complete, and remarks that ignorance of programming language concepts is the reason for many flaws in input formats.
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.
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.[25] Some languages, including Perl and Lisp, contain constructs that allow execution during the parsing phase. Languages that have constructs that allow the programmer to alter the behavior of the parser make syntax analysis an undecidable problem, and generally blur the distinction between parsing and execution.[26] In contrast to Lisp's macro system and Perl's BEGIN blocks, which may contain general computations, C macros are merely string replacements, and do not require code execution.[27]
Static semantics
The static semantics defines restrictions on the structure of valid texts that are hard or impossible to express in standard syntactic formalisms.[1] For compiled languages, static semantics essentially include those semantic rules that can be checked at compile time. Examples include checking that every identifier is declared before it is used (in languages that require such declarations) or that the labels on the arms of a case statement are distinct.[28] Many important restrictions of this type, like checking that identifiers are used in the appropriate context (e.g. not adding a integer to a function name), or that subroutine calls have the appropriate number and type of arguments can be enforced by defining them as rules in a logic called a type system. Other forms of static analyses like data flow analysis may also be part of static semantics. Newer programming languages like Java and C# have definite assignment analysis, a form of data flow analysis, as part of their static semantics.
Type system
Main articles: Type system and 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. The goal of a type system is to verify and usually enforce a certain level of correctness in programs written in that language by detecting certain incorrect operations. Any decidable type system involves a trade-off: while it rejects many incorrect programs, it can also prohibit some correct, albeit unusual programs. In order to bypass this downside, a number of languages have type loopholes, usually unchecked casts that may be used by the programmer to explicitly allow a normally disallowed operation between different types. In most typed languages, the type system is used only to type check programs, but a number of languages, usually functional ones, perform type inference, which relieves the programmer from writing type annotations. The formal design and study of type systems 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.[29] 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.[29] 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.[29] 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.[29]
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.[30]
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.[29] 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.[29] This can occasionally be useful, but it can also allow some kinds of program faults to go undetected at compile time and even at runtime.
Strong typing prevents the above. An attempt to perform an operation on the wrong type of value raises an error.[29] Strongly typed languages are often termed type-safe or safe.
An alternative definition for "weakly typed" refers to languages, such as Perl and JavaScript, 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.[31][32]
Execution semantics
Further information: Formal semantics of programming languages
Once data has been specified, the machine must be instructed to perform operations on the data. 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. The execution semantics (also known as dynamic semantics) of a language defines how and when the various constructs of a language should produce a program behavior. There are many ways of defining execution semantics. Natural language is often used to specify the execution semantics of languages commonly used in practice. A significant amount of academic research went into formal semantics of programming languages, which allow execution semantics to be specified in a formal manner. Results from this field of research have seen limited application to programming language design and implementation outside academia.
Many programming languages have some form of written specification of their syntax (form) and semantics (meaning). Some languages are defined by a specification document. For example, the C programming language is specified by an ISO Standard. Other languages, such as Perl, have a dominant implementation that is used as a reference.
The earliest programming languages predate the invention of the computer, and were used to direct the behavior of machines such as Jacquard looms and player pianos. Thousands of different programming languages have been created, mainly in the computer field, with many more being created every year. Most programming languages describe computation in an imperative style, i.e., as a sequence of commands, although some languages, such as those that support functional programming or logic programming, use alternative forms of description.
Definitions
A programming language is a notation for writing programs, which are specifications of a computation or algorithm.[1] Some, but not all, authors restrict the term "programming language" to those languages that can express all possible algorithms.[1][2] Traits often considered important for what constitutes a programming language include:
• Function and target: A computer programming language is a language[3] used to write computer programs, which involve a computer performing some kind of computation[4] or algorithm and possibly control external devices such as printers, disk drives, robots,[5] and so on. For example PostScript programs are frequently created by another program to control a computer printer or display. More generally, a programming language may describe computation on some, possibly abstract, machine. It is generally accepted that a complete specification for a programming language includes a description, possibly idealized, of a machine or processor for that language.[6] In most practical contexts, a programming language involves a computer; consequently programming languages are usually defined and studied this way.[7] 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.
• Abstractions: Programming languages usually contain abstractions for defining and manipulating data structures or controlling the flow of execution. The practical necessity that a programming language support adequate abstractions is expressed by the abstraction principle;[8] this principle is sometimes formulated as recommendation to the programmer to make proper use of such abstractions.[9]
• 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.[10][11]
Markup languages like XML, HTML or troff, which define structured data, are not generally considered programming languages.[12][13][14] Programming languages may, however, share the syntax with markup languages if a computational semantics is defined. XSLT, for example, is a Turing complete XML dialect.[15][16][17] Moreover, LaTeX, which is mostly used for structuring documents, also contains a Turing complete subset.[18][19]
The term computer language is sometimes used interchangeably with programming language.[20] However, the usage of both terms varies among authors, including the exact scope of each. One usage describes programming languages as a subset of computer languages.[21] In this vein, languages used in computing that have a different goal than expressing computer programs are generically designated computer languages. For instance, markup languages are sometimes referred to as computer languages to emphasize that they are not meant to be used for programming.[22] Another usage regards programming languages as theoretical constructs for programming abstract machines, and computer languages as the subset thereof that runs on physical computers, which have finite hardware resources.[23] John C. Reynolds emphasizes that formal specification languages are just as much programming languages as are the languages intended for execution. He also argues that textual and even graphical input formats that affect the behavior of a computer are programming languages, despite the fact they are commonly not Turing-complete, and remarks that ignorance of programming language concepts is the reason for many flaws in input formats.
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.
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.[25] Some languages, including Perl and Lisp, contain constructs that allow execution during the parsing phase. Languages that have constructs that allow the programmer to alter the behavior of the parser make syntax analysis an undecidable problem, and generally blur the distinction between parsing and execution.[26] In contrast to Lisp's macro system and Perl's BEGIN blocks, which may contain general computations, C macros are merely string replacements, and do not require code execution.[27]
Static semantics
The static semantics defines restrictions on the structure of valid texts that are hard or impossible to express in standard syntactic formalisms.[1] For compiled languages, static semantics essentially include those semantic rules that can be checked at compile time. Examples include checking that every identifier is declared before it is used (in languages that require such declarations) or that the labels on the arms of a case statement are distinct.[28] Many important restrictions of this type, like checking that identifiers are used in the appropriate context (e.g. not adding a integer to a function name), or that subroutine calls have the appropriate number and type of arguments can be enforced by defining them as rules in a logic called a type system. Other forms of static analyses like data flow analysis may also be part of static semantics. Newer programming languages like Java and C# have definite assignment analysis, a form of data flow analysis, as part of their static semantics.
Type system
Main articles: Type system and 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. The goal of a type system is to verify and usually enforce a certain level of correctness in programs written in that language by detecting certain incorrect operations. Any decidable type system involves a trade-off: while it rejects many incorrect programs, it can also prohibit some correct, albeit unusual programs. In order to bypass this downside, a number of languages have type loopholes, usually unchecked casts that may be used by the programmer to explicitly allow a normally disallowed operation between different types. In most typed languages, the type system is used only to type check programs, but a number of languages, usually functional ones, perform type inference, which relieves the programmer from writing type annotations. The formal design and study of type systems 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.[29] 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.[29] 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.[29] 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.[29]
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.[30]
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.[29] 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.[29] This can occasionally be useful, but it can also allow some kinds of program faults to go undetected at compile time and even at runtime.
Strong typing prevents the above. An attempt to perform an operation on the wrong type of value raises an error.[29] Strongly typed languages are often termed type-safe or safe.
An alternative definition for "weakly typed" refers to languages, such as Perl and JavaScript, 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.[31][32]
Execution semantics
Further information: Formal semantics of programming languages
Once data has been specified, the machine must be instructed to perform operations on the data. 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. The execution semantics (also known as dynamic semantics) of a language defines how and when the various constructs of a language should produce a program behavior. There are many ways of defining execution semantics. Natural language is often used to specify the execution semantics of languages commonly used in practice. A significant amount of academic research went into formal semantics of programming languages, which allow execution semantics to be specified in a formal manner. Results from this field of research have seen limited application to programming language design and implementation outside academia.
