Immutable Object - Background

Background

In imperative programming, values held in program variables whose content never changes are 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 potential 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 that 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 (weakly immutable). If all fields are immutable, then the object is immutable. If the whole object cannot be extended by another class, the object is called strongly 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) that 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 with mutable to be so.