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The heap data structure, specifically the binary heap, was introduced by J. W. J. Williams in 1964, as a data structure for the heapsort sorting algorithm. [3] Heaps are also crucial in several efficient graph algorithms such as Dijkstra's algorithm. When a heap is a complete binary tree, it has the smallest possible height—a heap with N ...
The heapsort algorithm can be divided into two phases: heap construction, and heap extraction. The heap is an implicit data structure which takes no space beyond the array of objects to be sorted; the array is interpreted as a complete binary tree where each array element is a node and each node's parent and child links are defined by simple arithmetic on the array indexes.
Contents. Binary heap. A binary heap is a heap data structure that takes the form of a binary tree. Binary heaps are a common way of implementing priority queues. [ 1 ]: 162–163 The binary heap was introduced by J. W. J. Williams in 1964, as a data structure for heapsort.
Heap pollution. In the Java programming language, heap pollution is a situation that arises when a variable of a parameterized type refers to an object that is not of that parameterized type. [1] This situation is normally detected during compilation and indicated with an unchecked warning. [1]
Leftist tree. In computer science, a leftist tree or leftist heap is a priority queue implemented with a variant of a binary heap. Every node x has an s-value which is the distance to the nearest leaf in subtree rooted at x. [1] In contrast to a binary heap, a leftist tree attempts to be very unbalanced.
Heap overflow. A heap overflow, heap overrun, or heap smashing is a type of buffer overflow that occurs in the heap data area. Heap overflows are exploitable in a different manner to that of stack-based overflows. Memory on the heap is dynamically allocated at runtime and typically contains program data. Exploitation is performed by corrupting ...
A min-max heap is a complete binary tree containing alternating min (or even) and max (or odd) levels. Even levels are for example 0, 2, 4, etc, and odd levels are respectively 1, 3, 5, etc. We assume in the next points that the root element is at the first level, i.e., 0. Example of Min-max heap.
Double-ended priority queue. In computer science, a double-ended priority queue (DEPQ)[1] or double-ended heap[2] is a data structure similar to a priority queue or heap, but allows for efficient removal of both the maximum and minimum, according to some ordering on the keys (items) stored in the structure.