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In computer science, primitive data types are a set of basic data types from which all other data types are constructed. [1] Specifically it often refers to the limited set of data representations in use by a particular processor, which all compiled programs must use.
String functions are used in computer programming languages to manipulate a string or query information about a string (some do both).. Most programming languages that have a string datatype will have some string functions although there may be other low-level ways within each language to handle strings directly.
Some of these languages with immutable strings also provide another type that is mutable, such as Java and .NET's StringBuilder, the thread-safe Java StringBuffer, and the Cocoa NSMutableString. There are both advantages and disadvantages to immutability: although immutable strings may require inefficiently creating many copies, they are ...
In C and C++, volatile is a type qualifier, like const, and is a part of a type (e.g. the type of a variable or field). The behavior of the volatile keyword in C and C++ is sometimes given in terms of suppressing optimizations of an optimizing compiler: 1- don't remove existing volatile reads and writes, 2- don't add new volatile reads and writes, and 3- don't reorder volatile reads and writes.
For a mutable C object, its mField can be written to. For a const(C) object, mField cannot be modified, it inherits const; iField is still immutable as it is the stronger guarantee. For an immutable(C), all fields are immutable. In a function like this:
Mutability becomes an issue when trying to create interoperability between pure functional and procedural languages. Languages like Haskell have no mutable types, whereas C++ does not provide such rigorous guarantees. Many functional types when bridged to object oriented languages can not guarantee that the underlying objects won't be modified.
In computing, a persistent data structure or not ephemeral data structure is a data structure that always preserves the previous version of itself when it is modified. Such data structures are effectively immutable, as their operations do not (visibly) update the structure in-place, but instead always yield a new updated structure.
In contrast, mutable objects can share state. Mutability allows better object reuse via the caching and re-initialization of old, unused objects. Sharing is usually nonviable when state is highly variable. Other primary concerns include retrieval (how the end-client accesses the flyweight), caching and concurrency.