Datatype |
In computer science, a datatype (often simply a type) is a name or label for a set of values and some operations which one can perform on that set of values. Programming languages implicitly or explicitly support one or more datatypes; these types may act as a statically or dynamically checked constraint on the computer programs generatable in a given language.
= Basis =
Assigning datatypes ( typing ) has the basic purpose of giving some semantic meaning to otherwise meaningless collections of Bits. Types usually have associations either with values in computer memory or with object (computer science)s such as variable (computer science)s. Because any value simply consists of a set of bits in a computer, hardware makes no distinction even between memory addresses, instruction code (programming), character (computing), integers and floating-point numbers. Types inform programs and programmers how they should treat those mere bits.
Major functions that type systems provide include:
Typically a program associates each value with one particular type (although a type may have more than one subtype). Other entities, such as objects, modules, communication channels, Dependency (computer science), or even types themselves, can become associated with a type. For example:
A type system , specified in each programming language, stipulates the ways typed programs may behave and makes behavior outside these rules illegal. An effect system typically provide more fine-grained control than a type system.
More formally, type theory studies type systems.
= Type checking =
The process of verifying and enforcing the constraints of types - type checking - may occur either at Compile time (a static check) or run-time (a dynamic check). Static type-checking becomes a primary task of the semantic analysis carried out by a Compiler. If a language enforces type rules strongly (that is, generally allowing only those automatic type conversions which do not lose information), one can refer to the process as strongly typed , if not, as weakly typed .
== Static and dynamic typing ==
In dynamic typing, type checking often takes place at Runtime because variables can aquire different types depending on the Execution (computers) path. Static type systems for dynamic types usually need to explicitly represent the concept of an execution path, and allow types to depend on it. This seems to require either a trivial or a cumbersome type system in order to work well.
C programming language, C plus plus, Java programming language, ML programming language, and Haskell programming language are statically typed, whereas Objective-C, Scheme programming language, Lisp programming language, Smalltalk, Perl programming language, PHP, Visual Basic programming language, Ruby programming language, and Python programming language, are dynamically typed. Dynamic typing is often associated with so-called scripting languages and other rapid application development environments. One tends to see dynamic types more often used in interpreted languages, whereas static types are used in compiled languages. See typed and untyped languages for the complete list of typed and untyped languages.
Duck typing is a humorous way of describing the (dynamic) typing typical of many scripting languages which guess the type of a value. Initially coined by Dave Thomas in the Ruby programming language community, its premise is that (referring to a value) if it walks like a duck, and quacks like a duck, then it is a duck .
To see how type checking works, consider the following Pseudocode example:
var x; // (1) x := 5; // (2) x := hi ; // (3)
In this example, (1) declares the name x; (2) associates the integer value 5 to the name x; and (3) associates the string value hi to the name x. In most statically typed systems, the above code fragment would be illegal, because (2) and (3) bind x to values of inconsistent type.
By contrast, a purely dynamically typed system would permit the above program to execute, because the name x would not have to have a consistent type. The implementation of a dynamically typed language will catch errors related to the misuse of values - type errors - at the time the erroneous statement or Expression (mathematics) is computed. In other words, dynamic typing catches errors during program execution . A typical implementation of dynamic typing will keep all program values tagged with a type, and check the type tag before any value is used in an operation. For example:
var x = 5; // (1) var y = hi ; // (2) var z = x + y; // (3)
In this code fragment, (1) binds the value 5 to x; (2) binds the value hi to y; and (3) attempts to add x to y. In a dynamically typed language, the value bound to x might be a pair (integral data type, 5), and the value bound to y might be a pair (string data type, hi ). When the program attempts to execute line 3, the language implementation would check the type tags integer and string, discover that the operation + (addition) is not defined over these two types, and signals an error.
Some statically typed languages have a back door in the language that enables programmers to write code that does not statically type check. For example, C and Java have cast (computer science) .
The presence of static typing in a programming language does not necessarily imply the absence of dynamic typing mechanisms. For example, Java is statically typed, but certain operations require the support of runtime type tests, which are a form of dynamic typing. See programming language for more discussion of the interactions between static and dynamic typing.
== Static and dynamic type checking in practice ==
The choice between static and dynamic typing requires some trade-offs. Many programmers strongly favor one over the other; some to the point of considering languages following the disfavored system to be unusable or crippled.
Static typing finds type errors reliably and at compile time. This should increase the reliability of the delivered program. However, programmers disagree over how commonly type errors occur, and thus what proportion of those bugs which are written would be caught by static typing. Static typing advocates believe programs are more reliable when they have been type-checked, while dynamic typing advocates point to distributed code that has proven reliable and to small bug databases. The value of static typing, then, presumably increases as the strength of the type system is increased. Advocates of strongly typed languages such as ML and Haskell have suggested that almost all bugs can be considered type errors, if the types used in a program are sufficiently well declared by the programmer or inferred by the compiler.
Static typing usually results in compiled code that executes more quickly. When the compiler knows the exact data types that are in use, it can produce machine code that just does the right thing. Further, compilers in statically typed languages can find shortcuts more easily. Some dynamically-typed languages such as Common Lisp allow optional type declarations for optimization for this very reason. Static typing makes this pervasive. See optimization (computer science).
Statically-typed languages which lack type inference – such as Java – require that programmers declare the types they intend a method or function to use. This can serve as additional documentation for the program, which the compiler will not permit the programmer to ignore or drift out of synchronization. However, a language can be statically typed without requiring type declarations, so this is not a consequence of static typing.
Static typing allows construction of libraries which are less likely to be accidentally misused by their users. This can be used as an additional mechanism for communicating the intentions of the library developer.
A static type system constrains the use of powerful language constructs more than it constrains less powerful ones. This makes powerful constructs harder to use, and thus places the burden of choosing the right tool for the problem on the shoulders of the programmer, who might otherwise prefer to use the most powerful tool available. Choosing overly powerful tools may cause additional performance, reliability or correctness problems, because there are Computational_complexity_theory on the properties that can be expected from powerful language constructs. For example, indiscriminate use of Recursion or global variables may cause well-documented adverse effects.
Dynamic typing allows constructs that would be illegal in some static type systems. For example, eval functions that execute arbitrary data as code are possible (however, the typing within that evaluated code might be static). Furthermore, dynamic typing accommodates transitional code and prototyping, such as allowing a string to be used in place of a data structure.
Dynamic typing allows debuggers to be more functional; in particular, the debugger can modify the code arbitrarily and let the program continue to run. Programmers in dynamic languages sometimes program in the debugger and thus have a shorter edit-compile-test-debug cycle. However, the need to use debuggers is considered by some to be a sign of design or development process problems.
Dynamic typing may allow compilers and interpreters to run more quickly, since there may be less checking to perform and less code to revisit when the source code changes. This, too, may reduce the edit-compile-test-debug cycle.
= Strong and weak typing =
Main article: strongly-typed programming language
A strongly typed language has several meanings; for a clearer discussion, see the main article on the topic. One definition involves it not allowing an operation to succeed on arguments which are of the wrong type. An example of the absence of strong typing is a C cast gone wrong; if you cast a value in C, not only is the compiler required to allow the code, but the runtime is expected to allow it as well. This allows C code to be compact and fast, but it can make debugging more difficult.
Sometimes the term memory-safe language (or just safe language ) is used to describe languages that do not allow undefined operations to occur. For example, a memory-safe language will also bounds checking.
Weak typing means that types are implicitly converted (or cast) when they are used. If we were to revisit the previous example:
var x = 5; // (1) var y = hi ; // (2) x + y; // (3)
If the code above were written in a weakly-typed language, such as Visual Basic programming language, the code would run, yielding the result 5hi . The number 5 is converted to the string 5 to make sense of the operation (the + operator is overloaded to mean both addition and concatenation). However, there are problems with such conversions when operators are overloaded in this way. For example, would the result of the following code be 9 or 54
var x = 5; var y = 4 ; x + y;
In contrast, the REXX language (which is weakly-typed because it only has one type) does not overload the + operator, and hence + always means addition. The equivalent of the first example would fail (one operand not a number), and the second would yield 9 , unambiguously. Careful language design has also allowed other languages to appear to be weakly-typed (through type inference and other techniques) for usability while preserving the type checking and protection offered by languages such as Java.
= Polymorphism and types =
The type system allows operations to be done relying on contexts by type. For example, in an arithmetic expression, a + b, if a and b are typed as
= Explicit or implicit declaration and inference =
Many static type systems, such as C s and Java s, require type declarations : the programmer must explicitly associate each variable with a particular type. Others, such as Haskell s, perform type inference : the compiler draws conclusions about the types of variables based on how the variables are used. For example, given a function f(x,y) in which x and y are added together, the compiler can infer that x and y must be numbers -- since addition is only defined for numbers. Therefore, any call to f elsewhere in the program that specifies a non-numeric type (such as a string or list) as an argument would be erroneous.
Numerical and string constants and expressions in code can and often do imply type in a particular context. For example, an expression 3.14 might imply that a type of floating-point while [1, 2, 3] might imply a list of integers; typically an array.
= Collections of types =
Types form natural collections that can often be indexed or listed to find specific types of the kind described.
= Specialized types =
There are many different special kinds of types, which are associated with particular kinds of instances.
= Compatibility, equivalence and substitutability =
The question of compatibility and equivalence becomes a complicated and controversial topic and relates to the problem of substitutability: that is, given type A and type B , are they equal types or compatible Can the value with type B be used in the place where the value of A
If type A is compatible with type B , A is a subtype of B while not always vice versa. The definition is known as the Liskov substitution principle.
Type conversion may take place in order to make a type compatible or substitutable in context.
There are two different type compatiility methods: name compatibility and structure compatibility. The term equivalence and compatibility mean the same thing. Name type compatibility means that two variables have compatible types only if they are in either the same decleration or in declarations that use same type name. Structure type compatibility means that two variables have compatible types if their type have identicle structure. There are some variations of these two methods, and most languages use combinations of the different techniques.
= See also =
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