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  2. Comparison of data structures - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data_structures

    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 ...

  3. Tree (abstract data type) - Wikipedia

    en.wikipedia.org/wiki/Tree_(abstract_data_type)

    The number of edges along the shortest path between two nodes. Level The level of a node is the number of edges along the unique path between it and the root node. [4] This is the same as depth. Width The number of nodes in a level. Breadth The number of leaves. Forest A set of one or more disjoint trees. Ordered tree

  4. 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.

  5. Opaque data type - Wikipedia

    en.wikipedia.org/wiki/Opaque_data_type

    In computer science, an opaque data type is a data type whose concrete data structure is not defined in an interface. This enforces information hiding , since its values can only be manipulated by calling subroutines that have access to the missing information.

  6. Abstraction (computer science) - Wikipedia

    en.wikipedia.org/wiki/Abstraction_(computer_science)

    The physical level describes complex low-level data structures in detail. Logical level – The next higher level of abstraction describes what data the database stores, and what relationships exist among those data. The logical level thus describes an entire database in terms of a small number of relatively simple structures.

  7. Lazy evaluation - Wikipedia

    en.wikipedia.org/wiki/Lazy_evaluation

    The ability to define control flow (structures) as abstractions instead of primitives. The ability to define potentially infinite data structures. This allows for more straightforward implementation of some algorithms. The ability to define partly-defined data structures where some elements are errors. This allows for rapid prototyping.

  8. 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.

  9. Binary tree - Wikipedia

    en.wikipedia.org/wiki/Binary_tree

    The number of different binary trees on nodes is , the th Catalan number (assuming we view trees with identical structure as identical). For large n {\displaystyle n} , this is about 4 n {\displaystyle 4^{n}} ; thus we need at least about log 2 ⁡ 4 n = 2 n {\displaystyle \log _{2}4^{n}=2n} bits to encode it.