'Heap order property discussed' presentation slideshows

Intuition for Asymptotic Notation

Intuition for Asymptotic Notation. Big-Oh f(n) is O(g(n)) if f(n) is asymptotically less than or equal to g(n) big-Omega f(n) is ?(g(n)) if f(n) is asymptotically greater than or equal to g(n) big-Theta f(n) is ?(g(n)) if f(n) is asymptotically equal to g(n) little-oh

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Chapter 8: Priority Queues and Heaps

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Heaps and Priority Queues

2. 5. 6. 9. 7. Heaps and Priority Queues. A priority queue stores a collection of items An item is a pair (key, element) Main methods of the Priority Queue ADT insertItem (k, o) inserts an item with key k and element o removeMin () removes the item with the smallest key.

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Heaps and Priority Queues

2. 5. 6. 9. 7. Heaps and Priority Queues. A priority queue stores a collection of items An item is a pair (key, element) Main methods of the Priority Queue ADT insertItem (k, o) inserts an item with key k and element o

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Heaps

Heaps. 2. 5. 6. 9. 7. A priority queue stores a collection of entries Each entry is a pair (key, value) Main methods of the Priority Queue ADT insert (k, x) inserts an entry with key k and value x removeMin () removes and returns the entry with smallest key. Additional methods

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Heaps

Heaps. 2. 5. 6. 9. 7. A priority queue stores a collection of entries Each entry is a pair (key, value) Main methods of the Priority Queue ADT insert (k, x) inserts an entry with key k and value x removeMin () removes and returns the entry with smallest key. Additional methods

362 views • 20 slides

Priority Queues and Heaps

Priority Queues and Heaps. 2. 5. 6. 9. 7. A priority queue stores a collection of entries Typically, an entry is a pair (key, value), where the key indicates the priority Main methods of the Priority Queue ADT insert (e) inserts an entry e

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Heaps

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Heaps

Heaps. 2. 5. 6. 9. 7. A heap is a binary tree storing keys at its nodes and satisfying the following properties: Heap-Order: for every internal node v other than the root, key ( v ) ? key ( parent ( v )) Complete Binary Tree: let h be the height of the heap

235 views • 10 slides