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A regular singly linked list only has efficient insertion and deletion at one end. However, a small modification—keeping a pointer to the last node in addition to the first one—will enable it to implement an efficient queue. A deque implemented using a modified dynamic array
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 ...
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 ...
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.
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.
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.
Using this method they obtain a structure that can maintain items with integer priorities in a range from 0 to a parameter C. The hot queue uses constant time per insertion or decrease-priority operation and amortized time O ( ( log C ) 1 / 3 ( log log C ) 1 / 2 ) {\displaystyle O((\log C)^{1/3}(\log \log C)^{1/2})} per extract-min ...
Nonetheless, for many purposes, the user can ignore these infidelities and simply use the implementation as if it were the abstract data type. Usually, there are many ways to implement the same ADT, using several different concrete data structures. Thus, for example, an abstract stack can be implemented by a linked list or by an array ...