Type safety
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In computer science, type safety is a property attributed to some, but not all, programming languages. The term is defined differently by different communities who use it — in particular, the formal type-theoretic definition is considerably stronger than what is understood by most programmers — but most uses have in common the notion of employing a type system to prevent certain forms of erroneous or undesirable program behavior (called type errors).
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 any given programming language are generally those that result from attempts to perform an operation, on some value (or values), that is not appropriate to its type (or their types). The fundamental basis for this classification is to a certain extent a matter of opinion: some language designers and programmers take the view 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 intent (as communicated via typing annotations) to be erroneous and deserving of the label "unsafe". 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 so-called memory safety (ie, restrictions 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, say t, such that there exists some sequence of bits (of the appropriate length) does not represent a legitimate member of t, if that language allows data to be copied into a variable of type t, then it is not type safe because such an operation might assign a non-t 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.
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[edit] Definitions
Robin Milner provided the following slogan to describe type safety:
- "Well-typed programs never go wrong."
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:
- (Type-) preservation
- "Well typedness" of programs remains invariant under the transition rules (i.e. evaluation rules or reduction rules) of the language.
- Progress
- A well typed program never gets "stuck", i.e., never gets into an undefined state where no further transitions are possible.
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.
[edit] 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, languages such as Standard ML, which has rigorously defined semantics, and Java, have been proved to be type safe[citation needed]. Some other languages such as Haskell are believed to be type safe. 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.
[edit] Memory management in type-safe languages
In order for a language to be completely type safe, it either needs to have garbage collection or place other restrictions on the allocation and de-allocation of memory (this section deals mainly with the former). Specifically, the language must not allow dangling pointers across structurally different types to exist. The reason is technical: suppose that a typed language (like Pascal) required that allocated memory had to be explicitly released. If a dangling pointer existed that still pointed to the old memory location, it is possible that a new data structure can get allocated in the same space with the slot the dangling pointer refers to now pointing to a different type. For example, if the pointer initially pointed to a structure with an integer field, but in the new object a pointer field was allocated in the place of the integer, then the pointer field could be changed to anything simply 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 itself is best done in a type-unsafe language or a language where type safety can be deactivated. C and C++ are often used.
[edit] Type safety and strong typing
Type safety is synonymous with one of the many definitions of strong typing; however, type safety and dynamic typing are not mutually exclusive. A dynamically typed language can be seen as a statically-typed language with a very permissive type system under which 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.
[edit] Type safety issues in specific languages
[edit] Ada
Ada was designed to be suitable for embedded systems, device drivers and other forms of system programming, but also to encourage type safe programming. To resolve these conflicting goals, Ada confines type-unsafety to a certain set of special constructs whose names usually begin with the string "Unchecked_". Unchecked_Deallocation can be effectively banned from a unit of Ada text by applying pragma Pure to this unit. It is expected that programmers will use "Unchecked_" constructs very carefully and only when necessary; programs that do not use them are type safe.
The SPARK programming language is a subset of Ada eliminating all its potential ambiguities and insecurities while at the same time adding statically checked contracts to the language features available. SPARK avoids the issues with dangling pointers by disallowing allocation at run time entirely.
[edit] C
The poster child of type-unsafe languages. While the language definition explicitly calls out the fact that behavior of 'type-unsafe' conversions is not defined, most implementations perform conversions that programmers find useful. The widespread use of C language idioms that make use of conversions has helped give it a reputation for being a type-unsafe language (the same kind of conversions can be performed in Ada using unchecked conversions, however this usage is much less common than in C).
[edit] Standard ML
SML has a rigorously defined semantics and is known to be type safe. However, some implementations of SML, including Standard ML of New Jersey (SML/NJ) and Mlton, provide libraries that offer certain unsafe operations. These facilities are often used in conjunction with those implementations' foreign function interfaces to interact with non-ML code (such as C libraries) that may require data laid out in specific ways. Another example is the SML/NJ interactive toplevel itself, which must use unsafe operations to execute ML code entered by the user.
[edit] Pascal
Pascal has had a number of type safety requirements, some of which are kept in some compilers. Where a Pascal compiler dictates "strict typing", two variables cannot be assigned to each other unless they are either compatible (such as conversion of integer to real) or assigned to the identical subtype. For example, if you have the following code fragment:
TYPE TwoTypes: I:Integer; Q:Real; END; TYPE DualTypes: I:Integer; Q:Real; END; VAR TT:TwoTypes; DT:DualTypes; TT1:TwoTypes; DT1:DualTypes;
Under strict typing, a variable defined as TwoTypes is not compatible with DualTypes (because they are not identical, even though the components of that user defined type are identical) and an assignment of TT := DT; is illegal. An assignment of TT := TT1; would be legal because the subtypes they are defined to are identical. However, an assignment such as TT.Q := DT.Q; would be legal.
[edit] See also
[edit] References
- Benjamin C. Pierce, Types and Programming Languages, MIT Press, 2002. (ISBN 0-262-16209-1) [1]
- Type Safe defined in the Portland Pattern Repository's Wiki [2]
- Andrew K. Wright and Matthias Felleisen, "A Syntactic Approach to Type Soundness," Information and Computation 115(1), pp. 38-94, 1994. [3]
- Stavros Macrakis, "Safety and power", ACM SIGSOFT Software Engineering Notes 7:2:25 (April 1982)requires subscription