CSC/ECE 517 Fall 2010/ch3 3i ls
Mixing static and dynamic code other than Ruby and Java
A programming language is a notation for writing programs, which are specifications of a computation or algorithm. Some, but not all, authors restrict the term "programming language" to those languages that can express all possible algorithms. 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.
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 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.
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, Lisp, JavaScript, and Python are dynamically typed.
The presence of static typing in a programming language does not necessarily imply the absence of all dynamic typing mechanisms. For example, Java, and various other object-oriented languages, while using static typing, require for certain operations, the support of runtime type tests, a form of dynamic typing.
As of the 4.0 Release, the .NET Framework supports a variant of dynamic typing via the System.Dynamic namespace whereby a static object of type 'dynamic' is a placeholder for the .NET runtime to interrogate its dynamic facilities to resolve the object reference.
Introduction
In computer science, a type system may be defined as a tractable syntactic framework for classifying phrases according to the kinds of values they compute. A type system associates types with each computed value. By examining the flow of these values, a type system attempts to prove that no type errors can occur. The type system in question determines what constitutes a type error, but a type system generally seeks to guarantee that operations expecting a certain kind of value are not used with values for which that operation makes no sense.
Assigning data types (typing) gives meaning to sequences of bits. Types usually have associations either with values in memory or with objects such as variables. Because any value simply consists of a sequence of bits in a computer, hardware makes no intrinsic distinction even between memory addresses, instruction code, characters, integers and floating-point numbers, being unable to discriminate between them based on bit pattern alone. Associating a sequence of bits and a type informs programs and programmers how that sequence of bits should be understood.
Major functions provided by type systems include:
- Safety: Use of types may allow a compiler to detect meaningless or probably invalid code.
- Optimization – Static type-checking may provide useful compile-time information.Optimization – Static type-checking may provide useful compile-time information.
- Abstraction (or modularity) – Types allow programmers to think about programs at a higher level than the bit or byte, not bothering with low-level implementation.
Type safety contributes to program correctness, but cannot guarantee it unless the type checking itself becomes an undecidable problem. Depending on the specific type system, a program may give the wrong result and be safely typed, producing no compiler errors. For instance, division by zero is not caught by the type checker in most programming languages; instead it is a runtime error. To prove the absence of more general defects, other kinds of formal methods, collectively known as program analysis, are in common use, as well as software testing—a widely used empirical method for finding errors that the type checker cannot detect.
Static Typing vs. Dynamic Typing
Static Typing
A programming language is said to use static typing when type checking is performed during compile-time as opposed to run-time. Statically typed languages include Ada, AS3, C, C++, C#, Eiffel, F#, Go, JADE, Java, Fortran, Haskell, ML, Objective-C, Pascal, Perl. They will reject some programs that may be well-behaved at run-time, but that cannot be statically determined to be well-typed. For example, even if an expression <complex test> always evaluates to true at run-time, a program containing the code
if <complex test> then 42 else <type error>
will be rejected as ill-typed, because a static analysis cannot determine that the else branch won't be taken.
Dynamic Typing
A programming language is said to be dynamically typed when the majority of its type checking is performed at run-time as opposed to at compile-time. In dynamic typing, values have types but variables do not; that is, a variable can refer to a value of any type. Dynamically typed languages include Erlang, Groovy, JavaScript, Lisp, Lua, Objective-C, Perl (with respect to user-defined types but not built-in types), PHP, Prolog, Python, Ruby, Smalltalk and Tcl. Compared to static typing, dynamic typing can be more flexible (e.g. by allowing programs to generate types and functionality based on run-time data), though at the expense of fewer a priori guarantees. This is because a dynamically typed language accepts and attempts to execute some programs which may be ruled as invalid by a static type checker. The term "dynamic language" means something different ("runtime dynamism") and a dynamic language is not necessarily dynamically typed.
Mixing Static and Dynamic Typing
The presence of static typing in a programming language does not necessarily imply the absence of all dynamic typing mechanisms. For example, Java, and various other object-oriented languages, while using static typing, require for certain operations (downcasting) the support of runtime type tests, a form of dynamic typing. See programming language for more discussion of the interactions between static and dynamic typing.
As of the 4.0 Release, the .NET Framework supports a variant of dynamic typing via the System.Dynamic namespace whereby a static object of type 'dynamic' is a placeholder for the .NET runtime to interrogate its dynamic facilities to resolve the object reference.
The choice between static and dynamic typing requires trade-offs.
Static typing can find type errors reliably 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 well 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 dependently typed languages such as Dependent ML and Epigram have suggested that almost all bugs can be considered type errors, if the types used in a program are properly declared by the programmer or correctly 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 optimized machine code. Further, compilers for statically typed languages can find assembler 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.
By contrast, dynamic typing may allow compilers to run more quickly and allow interpreters to dynamically load new code, since changes to source code in dynamically typed languages may result in less checking to perform and less code to revisit. This too may reduce the edit-compile-test-debug cycle.
Statically typed languages which lack type inference (such as Java and C) 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 permit to drift out of synchronization. However, a language can be statically typed without requiring type declarations (examples include Haskell, Scala and to a lesser extent C#), so this is not a necessary consequence of static typing.
Dynamic typing allows constructs that some static type checking would reject as illegal. For example, eval functions, which execute arbitrary data as code, become possible. Furthermore, dynamic typing better accommodates transitional code and prototyping, such as allowing a placeholder data structure (mock object) to be transparently used in place of a full-fledged data structure (usually for the purposes of experimentation and testing).
Dynamic typing is used in Duck typing which can support easier code reuse.
Dynamic typing typically makes metaprogramming more effective and easier to use. For example, C++ templates are typically more cumbersome to write than the equivalent Ruby or Python code.[citation needed] More advanced run-time constructs such as metaclasses and introspection are often more difficult to use in statically typed languages.
The following table shows the type system cross reference list.
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Programming Style
Some programmers prefer statically typed languages; others prefer dynamically typed languages. Statically typed languages alert programmers to type errors during compilation, and they may perform better at runtime. Advocates of dynamically typed languages claim they better support rapid prototyping and that type errors are only a small subset of errors in a program. Likewise, there is often no need to manually declare all types in statically typed languages with type inference; thus, the need for the programmer to explicitly specify types of variables is automatically lowered for such languages; and some dynamic languages have run-time optimisers that can generate fast code approaching the speed of static language compilers, often by using partial type inference.