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  2. Queue (abstract data type) - Wikipedia

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

    A queue has two ends, the top, which is the only position at which the push operation may occur, and the bottom, which is the only position at which the pop operation may occur. A queue may be implemented as circular buffers and linked lists, or by using both the stack pointer and the base pointer.

  3. 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 ...

  4. d-ary heap - Wikipedia

    en.wikipedia.org/wiki/D-ary_heap

    The d-ary heap consists of an array of n items, each of which has a priority associated with it. These items may be viewed as the nodes in a complete d-ary tree, listed in breadth first traversal order: the item at position 0 of the array (using zero-based numbering) forms the root of the tree, the items at positions 1 through d are its children, the next d 2 items are its grandchildren, etc.

  5. Linked list - Wikipedia

    en.wikipedia.org/wiki/Linked_list

    Linked lists are among the simplest and most common data structures. They can be used to implement several other common abstract data types, including lists, stacks, queues, associative arrays, and S-expressions, though it is not uncommon to implement those data structures directly without using a linked list as the basis.

  6. Fibonacci heap - Wikipedia

    en.wikipedia.org/wiki/Fibonacci_heap

    One such structure, the Brodal queue, [5] is, in the words of the creator, "quite complicated" and "[not] applicable in practice." Invented in 2012, the strict Fibonacci heap [ 6 ] is a simpler (compared to Brodal's) structure with the same worst-case bounds.

  7. Double-ended priority queue - Wikipedia

    en.wikipedia.org/wiki/Double-ended_priority_queue

    Implementing a DEPQ using interval heap. Apart from the above-mentioned correspondence methods, DEPQ's can be obtained efficiently using interval heaps. [6] An interval heap is like an embedded min-max heap in which each node contains two elements. It is a complete binary tree in which: [6] The left element is less than or equal to the right ...

  8. Priority queue - Wikipedia

    en.wikipedia.org/wiki/Priority_queue

    While priority queues are often implemented using heaps, they are conceptually distinct from heaps. A priority queue is an abstract data type like a list or a map; just as a list can be implemented with a linked list or with an array, a priority queue can be implemented with a heap or another method such as an ordered array.

  9. Binary heap - Wikipedia

    en.wikipedia.org/wiki/Binary_heap

    The best you can do is (in case of array implementation) simply concatenating the two heap arrays and build a heap of the result. [13] A heap on n elements can be merged with a heap on k elements using O(log n log k) key comparisons, or, in case of a pointer-based implementation, in O(log n log k) time. [14]