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</tr> </table> In computer science, type safety is a property of some programming languages that is defined differently by different communities, but most definitions involve the use of a type system to prevent certain erroneous or undesirable program behavior (called type errors). The formal type-theoretic definition is considerably stronger than what is understood by most programmers.
The enforcement can be static, catching potential errors at compile time, or dynamic, associating type information with values at run time and consulting them as needed to detect imminent errors, or a combination of both. Type safety is a property of the programming language, not of the programs themselves. For example, it is possible to write a safe program in a type-unsafe language.
The behaviors classified as type errors by a given programming language are usually those that result from attempts to perform operations on values that are not of the appropriate data type. This classification is partly based on opinion; some language designers and programmers argue that any operation not leading to program crashes, security flaws or other obvious failures is legitimate and need not be considered an error, while others consider any contravention of the programmer's explicit intent (as communicated via typing annotations) to be erroneous and not "type-safe."
In the context of static type systems, type safety usually involves (among other things) a guarantee that the eventual value of any expression will be a legitimate member of that expression's static type. The precise requirement is more subtle than this — see, for example, subtype and polymorphism for complications.
Type safety is closely linked to memory safety, a restriction on the ability to copy arbitrary bit patterns from one memory location to another. For instance, in an implementation of a language that has some type <math>t</math>, such that some sequence of bits (of the appropriate length) does not represent a legitimate member of <math>t</math>, if that language allows data to be copied into a variable of type <math>t</math>, then it is not type-safe because such an operation might assign a non-<math>t</math> value to that variable. Conversely, if the language is type-unsafe to the extent of allowing an arbitrary integer to be used as a pointer, then it is clearly not memory-safe.
Most statically typed languages provide a degree of type safety that is strictly stronger than memory safety, because their type systems enforce the proper use of abstract data types defined by programmers even when this is not strictly necessary for memory safety or for the prevention of any kind of catastrophic failure.
Robin Milner provided the following slogan to describe type safety:
The appropriate formalization of this slogan depends on the style of formal semantics used for a particular language. In the context of denotational semantics, type safety means that the value of an expression that is well-typed, say with type τ, is a bona fide member of the set corresponding to τ.
In 1994, Andrew Wright and Matthias Felleisen formulated what is now the standard definition and proof technique for type safety in languages defined by operational semantics. Under this approach, type safety is determined by two properties of the semantics of the programming language:
These properties do not exist in a vacuum; they are linked to the semantics of the programming language they describe, and there is a large space of varied languages that can fit these criteria, since the notion of "well typed" program is part of the static semantics of the programming language and the notion of "getting stuck" (or "going wrong") is a property of its dynamic semantics.
Vijay Saraswat provides the following definition:
Type-safe and type-unsafe languages
Type safety is usually a requirement for any toy language proposed in academic programming language research. Many languages, on the other hand, are too big for human-generated type-safety proofs, as they often require checking thousands of cases. Nevertheless, some languages such as Standard ML, which has rigorously defined semantics, have been proved to meet one definition of type safety. On the other hand, some languages, like Java, have been proved to not meet this definition of type safety. Some other languages such as Haskell are believed to meet some definition of type safety, provided certain "escape" features are not used (for example Haskell's unsafePerformIO, used to "escape" from the usual restricted environment in which I/O is possible, circumvents the type system and so can be used to break type safety.) Type punning is another example of such an "escape" feature. Regardless of the properties of the language definition, certain errors may occur at runtime due to bugs in the implementation, or in linked libraries written in other languages; such errors could render a given implementation type unsafe in certain circumstances.
Memory management in type-safe languages
To be type-safe, a language must have garbage collection or otherwise restrict the allocation and de-allocation of memory. Specifically, it must not allow dangling pointers across structurally different types. This is because if a typed language (like Pascal) required that allocated memory be explicitly released, and a dangling pointer still points to the old memory location, then a new data structure may be allocated in the same space with the slot the pointer refers to but point to a different type. For example, if the pointer initially points to a structure with an integer field, but in the new object a pointer field is allocated to the place of the integer, then the pointer field could be changed to anything by changing the value of the integer field (via dereferencing the dangling pointer). Because it is not specified what would happen when such a pointer is changed, the language is not type safe. Most type-safe languages satisfy these restrictions by using garbage collection to implement memory management.
Garbage collectors themselves are best implemented in languages that allow pointer arithmetic, so the library that implements the collector is best done in a type-unsafe language or a language where type safety can be deactivated. C and C++ are often used.
Type safety and strong typing
Type safety is synonymous with one of the many definitions of strong typing; but type safety and dynamic typing are mutually compatible. A dynamically typed language such as Smalltalk can be seen as a strongly typed language with a very permissive type system where any syntactically correct program is well-typed; as long as its dynamic semantics ensures that no such program ever "goes wrong" in an appropriate sense, it satisfies the definition above and can be called type-safe.
Type safety issues in specific languages