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  2. Queue (abstract data type) - Wikipedia

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

    The array size must be declared ahead of time, but some implementations simply double the declared array size when overflow occurs. Most modern languages with objects or pointers can implement or come with libraries for dynamic lists. Such data structures may have not specified a fixed capacity limit besides memory constraints.

  3. Circular buffer - Wikipedia

    en.wikipedia.org/wiki/Circular_buffer

    Circular buffering makes a good implementation strategy for a queue that has fixed maximum size. Should a maximum size be adopted for a queue, then a circular buffer is a completely ideal implementation; all queue operations are constant time. However, expanding a circular buffer requires shifting memory, which is comparatively costly.

  4. List of data structures - Wikipedia

    en.wikipedia.org/wiki/List_of_data_structures

    Array, a sequence of elements of the same type stored contiguously in memory; Record (also called a structure or struct), a collection of fields Product type (also called a tuple), a record in which the fields are not named; String, a sequence of characters representing text; Union, a datum which may be one of a set of types

  5. Semaphore (programming) - Wikipedia

    en.wikipedia.org/wiki/Semaphore_(programming)

    They communicate using a queue of maximum size N and are subject to the following conditions: the consumer must wait for the producer to produce something if the queue is empty; the producer must wait for the consumer to consume something if the queue is full.

  6. Dynamic array - Wikipedia

    en.wikipedia.org/wiki/Dynamic_array

    Elements can be removed from the end of a dynamic array in constant time, as no resizing is required. The number of elements used by the dynamic array contents is its logical size or size, while the size of the underlying array is called the dynamic array's capacity or physical size, which is the maximum possible size without relocating data. [2]

  7. Min-max heap - Wikipedia

    en.wikipedia.org/wiki/Min-max_heap

    This makes the min-max heap a very useful data structure to implement a double-ended priority queue. Like binary min-heaps and max-heaps, min-max heaps support logarithmic insertion and deletion and can be built in linear time. [3] Min-max heaps are often represented implicitly in an array; [4] hence it's referred to as an implicit data structure.

  8. Double-ended queue - Wikipedia

    en.wikipedia.org/wiki/Double-ended_queue

    The dynamic array approach uses a variant of a dynamic array that can grow from both ends, sometimes called array deques. These array deques have all the properties of a dynamic array, such as constant-time random access , good locality of reference , and inefficient insertion/removal in the middle, with the addition of amortized constant-time ...

  9. Bucket queue - Wikipedia

    en.wikipedia.org/wiki/Bucket_queue

    A bucket queue can handle elements with integer priorities in the range from 0 or 1 up to some known bound C, and operations that insert elements, change the priority of elements, or extract (find and remove) the element that has the minimum (or maximum) priority. It consists of an array A of container data structures; in most sources these ...