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In computer science, a heap is a tree-based data structure that satisfies the heap property: In a max heap, for any given node C, if P is the parent node of C, then the key (the value) of P is greater than or equal to the key of C. In a min heap, the key of P is less than or equal to the key of C. [1] The node at the "top" of the heap (with no ...
Some collections maintain a linear ordering of items – with access to one or both ends. The data structure implementing such a collection need not be linear. For example, a priority queue is often implemented as a heap, which is a kind of tree. Notable linear collections include: list; stack; queue; priority queue; double-ended queue
Splay trees and treaps are self-balancing but not height-balanced, as their height is not guaranteed to be logarithmic in the number of items. Self-balancing binary search trees provide efficient implementations for mutable ordered lists, and can be used for other abstract data structures such as associative arrays, priority queues and sets.
Heap files are lists of unordered records of variable size. Although sharing a similar name, heap files are widely different from in-memory heaps. In-memory heaps are ordered, as opposed to heap files. Simplest and most basic method insert efficient, with new records added at the end of the file, providing chronological order
The general heap order must be enforced; Every operation (add, remove_min, merge) on two skew heaps must be done using a special skew heap merge. A skew heap is a self-adjusting form of a leftist heap which attempts to maintain balance by unconditionally swapping all nodes in the merge path when merging two heaps. (The merge operation is also ...
Some additional operations that can be implemented for the meldable heap that also have O(logn) worst-case efficiency are: Remove(u) - Remove the node u and its key from the heap. Absorb(Q) - Add all elements of the meldable heap Q to this heap, emptying Q in the process. DecreaseKey(u, y) - Decreases the key in node u to y (pre-condition: y ...
In a weak max-heap, the maximum value can be found (in constant time) as the value associated with the root node; similarly, in a weak min-heap, the minimum value can be found at the root. As with binary heaps, weak heaps can support the typical operations of a priority queue data structure: insert, delete-min, delete, or decrease-key, in ...
The kinetic hanger structure (including certificates and event queue) is exactly the same as the kinetic heap structure, but without the balancing requirement. Thus, it consists of an efficient priority queue (the event queue) to maintain the certificate failure times, as well as a main (not necessarily balanced) heap-like tree structure in which the elements are stored.