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In object-oriented programming, "immutable interface" is a pattern for designing an immutable object. [1] The immutable interface pattern involves defining a type which does not provide any methods which mutate state. Objects which are referenced by that type are not seen to have any mutable state, and appear immutable.
Both Java and the .NET Framework have mutable versions of string. In Java [5]: 84 these are StringBuffer and StringBuilder (mutable versions of Java String) and in .NET this is StringBuilder (mutable version of .Net String). Python 3 has a mutable string (bytes) variant, named bytearray. [6] Additionally, all of the primitive wrapper classes in ...
The relatively new System.Collections.Immutable package, available in .NET Framework versions 4.5 and above, and in all versions of .NET Core, also includes the System.Collections.Immutable.Dictionary<TKey, TValue> type, which is implemented using an AVL tree. The methods that would normally mutate the object in-place instead return a new ...
There are multiple ways to implement the flyweight pattern. One example is mutability: whether the objects storing extrinsic flyweight state can change. Immutable objects are easily shared, but require creating new extrinsic objects whenever a change in state occurs. In contrast, mutable objects can share state.
Final variables can be used to construct trees of immutable objects. Once constructed, these objects are guaranteed not to change anymore. To achieve this, an immutable class must only have final fields, and these final fields may only have immutable types themselves. Java's primitive types are immutable, as are strings and several other classes.
JavaBeans are inherently mutable and so lack the advantages offered by immutable objects. [ 1 ] Having to create getters for every property and setters for many, most, or all of them can lead to an immense quantity of boilerplate code .
The tail will not be duplicated, instead becoming shared between both the old list and the new list. So long as the contents of the tail are immutable, this sharing will be invisible to the program. Many common reference-based data structures, such as red–black trees, [7] stacks, [8] and treaps, [9] can easily be adapted to create a ...
The main difference between an arbitrary data structure and a purely functional one is that the latter is (strongly) immutable. This restriction ensures the data structure possesses the advantages of immutable objects: (full) persistency, quick copy of objects, and thread safety.