The Department of Computer Science & Engineering

CSE 116
Introduction To Computer Science for Majors 2
Lecture B
Lecture Notes
Stuart C. Shapiro
Spring, 2003


Riley Chapter 9

A Heap is a binary tree with the following properties:
  1. It is complete, i.e. full, except possibly for some right-most nodes at the highest level (at the bottom of the tree).
  2. The value of the root is greater than (or equal to, if duplicates are allowed) the values of all other nodes.

Complete binary trees are particularly easy to represent in arrays. Number the nodes by level:

Note that: So any complete binary tree containing n nodes can be represented in an array, a of n elements, where a[i] contains the value of the ith node, numbered as above.

Making a Heap
To turn an arbitrary complete binary tree into a heap, visit the nodes breadth-first (level by level, left to right == in order of their position in the array), and use the insertion algorithm (from the insertion sort) to "promote" each value up its branch. Running time is O(n log n).
Example [Riley, p. 410-411]:

Heap as Priority Queue
Insert by adding to end (as array), and promoting. Running time is O(log n).

First element is the root (index 0). Running time is O(1).

Delete and return first element.
Then go top-down to find correct position for value of old last node.
Fill an empty branch node with the maximum of the old last element and the child nodes.
Running time is O(log n).



Heap Sorting
Given an array:
  1. Make it into a heap.
  2. While the heap is non-empty
    1. Let v be result of delete.
    2. Put v in old last position.
Running time is O(n log n).


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Copyright © 2003 by Stuart C. Shapiro. All rights reserved.
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