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  2. List of data structures - Wikipedia

    en.wikipedia.org/wiki/List_of_data_structures

    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.

  3. Data structure - Wikipedia

    en.wikipedia.org/wiki/Data_structure

    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.

  4. Comparison of data structures - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data_structures

    meld: joining two heaps to form a valid new heap containing all the elements of both, destroying the original heaps. 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.

  5. Segment tree - Wikipedia

    en.wikipedia.org/wiki/Segment_tree

    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. [1]

  6. 2–3–4 tree - Wikipedia

    en.wikipedia.org/wiki/2–3–4_tree

    In computer science, a 2–3–4 tree (also called a 2–4 tree) is a self-balancing data structure that can be used to implement dictionaries. The numbers mean a tree where every node with children (internal node) has either two, three, or four child nodes: a 2-node has one data element, and if internal has two child nodes;

  7. Persistent data structure - Wikipedia

    en.wikipedia.org/wiki/Persistent_data_structure

    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.

  8. Priority queue - Wikipedia

    en.wikipedia.org/wiki/Priority_queue

    It implements a max-priority-queue, and has three parameters: a comparison object for sorting such as a function object (defaults to less<T> if unspecified), the underlying container for storing the data structures (defaults to std::vector<T>), and two iterators to the beginning and end of a sequence.

  9. Linked list - Wikipedia

    en.wikipedia.org/wiki/Linked_list

    In general, if a set of data structures needs to be included in linked lists, external storage is the best approach. If a set of data structures need to be included in only one linked list, then internal storage is slightly better, unless a generic linked list package using external storage is available.