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  2. Comparison of data structures - Wikipedia

    en.wikipedia.org/wiki/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.

  3. Container (abstract data type) - Wikipedia

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

    In computer science, a container is a class or a data structure [1] [2] whose instances are collections of other objects. In other words, they store objects in an organized way that follows specific access rules. The size of the container depends on the number of objects (elements) it contains.

  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. Abstract data type - Wikipedia

    en.wikipedia.org/wiki/Abstract_data_type

    The implementation of the module—namely, the bodies of the procedures and the concrete data structure used—can then be hidden from most clients of the module. This makes it possible to change the implementation without affecting the clients. If the implementation is exposed, it is known instead as a transparent data type.

  6. Java collections framework - Wikipedia

    en.wikipedia.org/wiki/Java_collections_framework

    java.util.Collection class and interface hierarchy Java's java.util.Map class and interface hierarchy. The Java collections framework is a set of classes and interfaces that implement commonly reusable collection data structures. [1] Although referred to as a framework, it works in a manner of a library. The collections framework provides both ...

  7. Concurrent data structure - Wikipedia

    en.wikipedia.org/wiki/Concurrent_data_structure

    Concurrent data structures are significantly more difficult to design and to verify as being correct than their sequential counterparts. The primary source of this additional difficulty is concurrency, exacerbated by the fact that threads must be thought of as being completely asynchronous: they are subject to operating system preemption, page faults, interrupts, and so on.

  8. Tree (abstract data type) - Wikipedia

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

    In computer science, a tree is a widely used abstract data type that represents a hierarchical tree structure with a set of connected nodes. Each node in the tree can be connected to many children (depending on the type of tree), but must be connected to exactly one parent, [ 1 ] [ 2 ] except for the root node, which has no parent (i.e., the ...

  9. Array (data structure) - Wikipedia

    en.wikipedia.org/wiki/Array_(data_structure)

    For that reason, the elements of an array data structure are required to have the same size and should use the same data representation. The set of valid index tuples and the addresses of the elements (and hence the element addressing formula) are usually, [3] [5] but not always, [2] fixed while the array is in use.