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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.
Dictionary of Algorithms and Data Structures. National Institute of Standards and Technology; Antonakos, James L.; Mansfield, Kenneth C. Jr. (1999). Practical Data Structures Using C/C++. Prentice-Hall. pp. 165–190. ISBN 0-13-280843-9. Collins, William J. (2005) [2002]. Data Structures and the Java Collections Framework.
Modern C++ compilers are tuned to minimize abstraction penalties arising from heavy use of the STL. 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.
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.
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 C++ Standard Library includes the Standard Template Library or STL that provides a framework of templates for common data structures and algorithms. Templates in C++ may also be used for template metaprogramming, which is a way of pre-evaluating some of the code at compile-time rather than run-time.
Furthermore, cache-optimization, usually via cache-aware or cache-oblivious data structures and algorithms, can often lead to orders of magnitude improvements in performance as well as avoiding time-complexity degeneracy that is characteristic of many cache-pessimizing algorithms, and is therefore one of the most important forms of optimization ...
The Library of Efficient Data types and Algorithms (LEDA) is a proprietarily-licensed software library providing C++ implementations of a broad variety of algorithms for graph theory and computational geometry. [1] It was originally developed by the Max Planck Institute for Informatics Saarbrücken. [2]
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