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This is a list of well-known data structures. For a wider list of terms, see list of terms relating to algorithms and data structures. For a comparison of running times for a subset of this list see comparison of data structures.
With the advent of C++11 the rule of three can be broadened to the rule of five (also known as "the rule of the big five" [5]) as C++11 implements move semantics, [6] allowing destination objects to grab (or steal) data from temporary objects. The following example also shows the new moving members: move constructor and move assignment operator.
A data structure known as a hash table.. In computer science, a data structure is a data organization and storage format that is usually chosen for efficient access to data. [1] [2] [3] More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data, [4] i.e., it is an algebraic structure about data.
This diagram represents five contiguous memory regions which each hold a pointer and a data block. The List Head points to the 2nd element, which points to the 5th, which points to the 3rd, thereby forming a linked list of available memory regions. A free list (or freelist) is a data structure used in a scheme for dynamic memory allocation.
The STL was created as the first library of generic algorithms and data structures for C++, with four ideas in mind: generic programming, abstractness without loss of efficiency, the Von Neumann computation model, [2] and value semantics. The STL and the C++ Standard Library are two distinct entities. [3]
Here are time complexities [5] of various heap data structures. The abbreviation am. indicates that the given complexity is amortized, otherwise it is a worst-case complexity. For the meaning of "O(f)" and "Θ(f)" see Big O notation. Names of operations assume a max-heap.
The zipper technique is general in the sense that it can be adapted to lists, trees, and other recursively defined data structures. Such modified data structures are usually referred to as "a tree with zipper" or "a list with zipper" to emphasize that the structure is conceptually a tree or list, while the zipper is a detail of the implementation.
This technique is simple and fast, with each dictionary operation taking constant time. However, the space requirement for this structure is the size of the entire keyspace, making it impractical unless the keyspace is small. [5] The two major approaches for implementing dictionaries are a hash table or a search tree. [3] [4] [5] [6]