Immutable object: Wikis


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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.



Before the advent of OOP, values held in program variables whose content never changed were known as 'constants' to differentiate them from variables that could be altered during execution. Examples might include conversion factors from kilogram weights to pounds or the value of Pi to several decimal places. 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 short 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.

Sometimes one talks of certain fields of an object being immutable. This means that there is no way to change those parts of the object state, even though other parts of the object may be changeable. (If all fields are immutable then the object is immutable.) This might, for example, help to explicitly enforce certain invariants about certain data in the object staying the same through the lifetime of the object. In some languages, this is done with a keyword (e.g. "const" in C++, "final" in Java) which designates the field to be immutable. In some languages, it is reversed -- in OCaml, fields of an object or record are by default immutable, and need to be explicitly marked "mutable" to be mutable.


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 they 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 String class.

String s = "ABC";

The method toLowerCase() will not change the data "ABC" that s 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 toLowerCase() method. To make the String s contain the data "abc", a different approach is needed.

s = s.toLowerCase();

Now the String s 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.

class Cart {
   private final List items;
   public Cart(List items) { this.items = items; }
   public List getItems() { return items; }
   public int total() { /* return sum of the prices */ }

An instance of this class is not immutable: one can add or remove items either by obtaining the field items by calling getItems() 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 ImmutableCart 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.

class ImmutableCart {
   private final List items;
   public ImmutableCart(List items) {
     this.items = Collections.unmodifiableList(new ArrayList(items));
   public List getItems() {
     return items;
   public int total() { /* return sum of the prices */ }


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

template<typename T>
class Cart {
   std::vector<T> items;
   Cart(const std::vector<T>& v): items(v) { }
   std::vector<T>& getItems() { return items; }
   const std::vector<T>& getItems() const { return items; }
   int total() const { /* return sum of the prices */ }


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

class Immutable(object):
     """An immutable class with a single attribute 'value'."""
     def __setattr__(self, *args):
         raise TypeError("can't modify immutable instance")
     __delattr__ = __setattr__
     def __init__(self, value):
         # we can no longer use self.value = value to store the instance data
         # so we must explicitly call the superclass
         super(Immutable, self).__setattr__('value', value)


In Scala any variable can be defined as mutable or immutable: simply in the declaration one can use val for immutable objects and var for mutable ones.

E.g. the following code snippet:

val maxValue = 100
var currentValue = 1

defines an immutable entity maxValue (the integer type is inferred at compile time) and a mutable entity named currentValue.

Actually one should talk about variables only for the mutable objects, and call the immutable entities values or constants.


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 while still correctly handling anything an application program might do.


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 String) and in .NET this is StringBuilder (mutable version of .Net String). Python 3 will have a mutable string (bytes) variant, named buffer.

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 [1]), 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.

See also

External links

This article contains some material from the Perl Design Patterns Book.


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