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# Binary Search Trees - PowerPoint PPT Presentation

Binary Search Trees. 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

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

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### Binary Search Trees

• 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 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.

• Need to map Items to a numerical value

• Integers

• Value(x) = x

• People

• Value(x) = ssn

• Value(x) = student id

• 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

• Constructor

• Insert

• Find

• Findmin

• Findmax

• Remove

• 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

}

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

}

• 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.

6

6

6

2

8

3

8

3

8

1

1

1

5

5

5

3

3

3

4

4

4

private BinaryNode remove( Comparable x, BinaryNode t )

{

if( t == null )

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;

}

• 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

• 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.

• 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.

N = 4

IPL = 1 + 1 + 2 = 4

1

1

2

N = 4

IPL = 1 + 2 + 3 = 6

1

2

3

1

1

2

2

3

Average IPL for N nodesN = 4

• Calculate IPL of all possible trees

1

2

2

• 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).

• Simple to understand

• Works for small datasets

• Basis for more complicated trees

• Using inheritance can implement

• AVL trees

• Splay trees

• Red Black trees