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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.
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.
Discrete mathematics - Study of discrete structures. Used in digital computer systems. Graph theory – Foundations for data structures and searching algorithms. Mathematical logic – Boolean logic and other ways of modeling logical queries; the uses and limitations of formal proof methods. Number theory – Theory of the integers.
The NIST Dictionary of Algorithms and Data Structures [1] is a reference work maintained by the U.S. National Institute of Standards and Technology. It defines a large number of terms relating to algorithms and data structures. For algorithms and data structures not necessarily mentioned here, see list of algorithms and list of data structures.
As in any tree-based data structure, the M-tree is composed of nodes and leaves. In each node there is a data object that identifies it uniquely and a pointer to a sub-tree where its children reside. Every leaf has several data objects. For each node there is a radius that defines a Ball in the desired metric space.
For a more comprehensive listing of data structures, see List of data structures. The comparisons in this article are organized by abstract data type . As a single concrete data structure may be used to implement many abstract data types, some data structures may appear in multiple comparisons (for example, a hash map can be used to implement ...
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In computer science, a Judy array is a data structure implementing a type of associative array with high performance and low memory usage. [1] Unlike most other key-value stores, Judy arrays use no hashing, leverage compression on their keys (which may be integers or strings), and can efficiently represent sparse data; that is, they may have large ranges of unassigned indices without greatly ...