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## PowerPoint Slideshow about ' Binary Search Trees' - kishi

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BST Properties

- Have all properties of binary tree
- Items in left subtree are smaller than items in any node
- Items in right subtree are larger than items in any node

Items

- Items must be comparable
- All items have a unique value
- Given two distinct items x and y either
- value(x) < value(y)
- value(x) > value(y)

- If value(x) = value(y) then x = y
- It will simplify programming to assume there are no duplicates in our set of items.

Items

- Need to map Items to a numerical value
- Integers
- Value(x) = x

- People
- Value(x) = ssn
- Value(x) = student id

Comparable Interface

- Want general tree code
- Requirement of item is that it supports
- <
- >
- =

- Java uses Interfaces for implementation
- Similar to abstract method
- Specify a method that using class is responsible for

BST Operations

- Constructor
- Insert
- Find
- Findmin
- Findmax

- Remove

BST Operations

- Generally Recursive

BinaryNode operation( Comparable x, BinaryNode t ) {

// End of path

if( t == null )

return null;

if( x.compareTo( t.element ) < 0 )

return operation( x, t.left );

else if( x.compareTo( t.element ) > 0 )

return operation( x, t.right );

else

return t; // Match

}

BST Find Method

private BinaryNode find( Comparable x, BinaryNode t )

{

if( t == null )

return null;

if( x.compareTo( t.element ) < 0 )

return find( x, t.left );

else if( x.compareTo( t.element ) > 0 )

return find( x, t.right );

else

return t; // Match

}

BST Remove Operations

- Remove
- Node is leaf
- Remove node

- Node has one child
- Replace node with child

- Node has two children
- Replace node with smallest child of right subtree.

- Node is leaf

Remove method

private BinaryNode remove( Comparable x, BinaryNode t )

{

if( t == null )

return t; // Item not found; do nothing

if( x.compareTo( t.element ) < 0 )

t.left = remove( x, t.left );

else if( x.compareTo( t.element ) > 0 )

t.right = remove( x, t.right );

else if( t.left != null && t.right != null ) // Two children

{

t.element = findMin( t.right ).element;

t.right = remove( t.element, t.right );

}

else

t = ( t.left != null ) ? t.left : t.right;

return t;

}

Internal Path Length

- Review depth/height
- Depth
- Depth is number of path segments from root to node
- Depth of node is distance from root to that node.
- Depth is unique
- Depth of root is 0

Internal Path Length

- Height
- Height is maximum distance from node to a leaf.
- There can be many paths from a node to a leaf.
- The height of the tree is another way of saying height of the root.

Internal Path Length

- IPL is the sum of the depths of all the nodes in a tree
- It gives a measure of how well balanced the tree is.

BST Efficiency

- If tree is balanced O(log(n))
- No guarantee that tree will be balanced
- Analysis in book suggests on IPL = O(nlog(n))
- This analysis is based on the assumption that all trees are equally likely
- Could always get the worst case (a degenerate tree).

Where do BST fit in

- Simple to understand
- Works for small datasets
- Basis for more complicated trees
- Using inheritance can implement
- AVL trees
- Splay trees
- Red Black trees

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