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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.
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 schematic picture of the skip list data structure. Each box with an arrow represents a pointer and a row is a linked list giving a sparse subsequence; the numbered boxes (in yellow) at the bottom represent the ordered data sequence.
Suffix trees are powerful data structures that have wide application in areas of pattern and string matching, indexing and textual statistics. However, it occupies a significant amount of space and thus has a drawback in many real-time applications that require processing a considerably large amount of data like genome analysis.
A class in C++ is a user-defined type or data structure declared with any of the keywords class, struct or union (the first two are collectively referred to as non-union classes) that has data and functions (also called member variables and member functions) as its members whose access is governed by the three access specifiers private, protected or public.
In computer science, a binomial heap is a data structure that acts as a priority queue.It is an example of a mergeable heap (also called meldable heap), as it supports merging two heaps in logarithmic time.
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.
A similar data structure is the interval tree. A segment tree for a set I of n intervals uses O ( n log n ) storage and can be built in O ( n log n ) time. Segment trees support searching for all the intervals that contain a query point in time O (log n + k ), k being the number of retrieved intervals or segments.