Immutable object

In object-oriented and functional programming, an immutable object is an object whose state cannot be modified after it is created. This is in contrast to a mutable object, which can be modified after it is created. An object can be either entirely immutable or some attributes in the object may be declared immutable; for example, using the const member data attribute in the C++ programming language. In some cases, an object is considered immutable even if some internally used attributes change but the object's state appears to be unchanging from an external point of view. For example, an object that uses memoization to cache the results of expensive computations could still be considered an immutable object. The initial state of an immutable object is usually set at its inception, but can also be set before actual use of the object.

Immutable objects are often useful because some costly operations for copying and comparing can be omitted, simplifying the program code and speeding execution. However, making an object immutable is usually inappropriate if the object contains a large amount of changeable data. Because of this, many languages allow for both immutable and mutable objects.

Background
In most object-oriented languages, objects can be referred to using references. Some examples of such languages are Java, C++,C#,VB.NET and many scripting languages, such as Python and Ruby. In this case, it matters whether the state of an object can vary when objects are shared via references.

If an object is known to be immutable, it can be copied simply by making a copy of a reference to it instead of copying the entire object. Because a reference (typically only the size of a pointer) is usually much smaller than the object itself, this results in memory savings and a boost in execution speed.

The reference copying technique is much more difficult to use for mutable objects, because if any user of a reference to a mutable object changes it, all other users of that reference will see the change. If this is not the intended effect, it can be difficult to notify the other users to have them respond correctly. In these situations, defensive copying of the entire object rather than the reference is usually an easy but costly solution. The observer pattern is an alternative technique for handling changes to mutable objects.

Immutable objects can be useful in multi-threaded applications. Multiple threads can act on data represented by immutable objects without concern of the data being changed by other threads. Immutable objects are therefore considered to be more thread-safe than mutable objects.

The practice of always using references in place of copies of equal objects is known as interning. If interning is used, two objects are considered equal if and only if their references, typically represented as integers, are equal. Some languages do this automatically: for example, Python automatically interns strings. If the algorithm which implements interning is guaranteed to do so in every case that it is possible, then comparing objects for equality is reduced to comparing their pointers, a substantial gain in speed in most applications. (Even if the algorithm is not guaranteed to be comprehensive, there still exists the possibility of a fast path case improvement when the objects are equal and use the same reference.) Interning is generally only useful for immutable objects.

Implementation
Immutability does not imply that the object as stored in the computer's memory is unwriteable. Rather, immutability is a compile-time construct that indicates what a programmer should do, not necessarily what he can do (for instance, by circumventing the type system or violating const correctness in C or C++).

A classic example of an immutable object is an instance of the Java  class.

The method  will not change the data "ABC" that   contains. Instead, a new String object is instantiated and given the data "abc" during its construction. A reference to this String object is returned by the  method. To make the String  contain the data "abc", a different approach is needed.

Now the String  references a new String object that contains "abc". The String class's methods never affect the data that a String object contains.

For an object to be immutable, there has to be no way to change fields, mutable or not, and to access fields that are mutable. Here is an example of a mutable object written in the Java programming language.

An instance of this class is not immutable: one can add or remove items either by obtaining the field  by calling   or by retaining a reference to the List object passed when an object of this class is created. The following change partially solves this problem. In the  class, the list is immutable: you cannot add or remove items. However, there is no guarantee that the items are also immutable. One solution is to use the decorator pattern as a wrapper around each of the list's items to make them also immutable.

In C++, a const-correct implementation of  would allow the user to declare new instances of the class as either   (immutable) or mutable, as desired, by providing two different versions of the   method. (Notice that in C++ it is not necessary &mdash; and in fact impossible &mdash; to provide a specialized constructor for  instances.)

In Python some built-in types are immutable, but custom classes are generally mutable. To create an immutable class, one should override attribute setting and deletion to raise exceptions:

A technique which blends the advantages of mutable and immutable objects, and is supported directly in almost all modern hardware, is copy-on-write (COW). Using this technique, when a user asks the system to copy an object, it will instead merely create a new reference which still points to the same object. As soon as a user modifies the object through a particular reference, the system makes a real copy and sets the reference to refer to the new copy. The other users are unaffected, because they still refer to the original object. Therefore, under COW, all users appear to have a mutable version of their objects, although in the case that users do not modify their objects, the space-saving and speed advantages of immutable objects are preserved. Copy-on-write is popular in virtual memory systems because it allows them to save memory space in the core while still correctly handling anything an application program might do.

Usage
Strings and other concrete objects are typically expressed as immutable objects to improve readability and runtime efficiency in object-oriented programming. In Python, Java and the .NET Framework, strings are immutable objects. Both Java and the .NET Framework have mutable versions of string. In Java these are StringBuffer and StringBuilder (mutable versions of Java ) and in .NET this is StringBuilder (mutable version of .Net String). Python 3 will have a mutable string (bytes) variant, named.

Additionally, all of the primitive wrapper classes in Java are immutable.

Enforcement of the pattern can be checked by using specialized compilers (see for example ), and there is a proposal to add immutable types to Java.

Similar patterns are the Immutable Interface and Immutable Wrapper.

In pure functional programming languages it is not possible to create mutable objects, so all objects are immutable.