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Tree Data Structures Tree Data Structures

Tree Data Structures - PowerPoint Presentation

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Uploaded On 2017-06-28

Tree Data Structures - PPT Presentation

Topics to be discussed Trees Data Structures Trees Binary Search Trees Tree traversal Types of Binary Trees Threaded binary trees Applications Trees Data Structures Tree Nodes Each node can have 0 or more ID: 564023

tree binary traversal trees binary tree trees traversal node expression left search nodes values order recursive null types links level structures data

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Presentation Transcript

Slide1

Tree Data StructuresSlide2

Topics to be discussed….

Trees Data Structures

Trees

Binary Search Trees

Tree traversal

Types of Binary Trees

Threaded binary trees

Applications Slide3

Trees Data Structures

Tree

Nodes

Each node can have 0 or more

childrenA node can have at most one parentBinary treeTree with 0–2 children per node

Tree

Binary Tree

backSlide4

Trees

Terminology

Root

no parentLeaf 

no childInterior

non-leafHeight

distance from root to leaf

Root node

Leaf nodes

Interior nodes

HeightSlide5

Level and Depth

Level

1

2

3

4

node

(13)

degree of a nodeleaf (terminal)

Non terminalparent

childrensiblingdegree of a tree

(3)

ancestorlevel of a nodeheight of a tree

(4)

3

2

1

3

2

0

0

1

0

0

0

0

0

1

2

2

2

3

3

3

3

3

3

4

4

4Slide6

Arithmetic Expression Using BT

+

*

A

*

/

E

D

C

B

inorder traversal

A / B * C * D + E

infix expression

preorder traversal

+ * * / A B C D E

prefix expression

postorder traversal

A B / C * D * E +

postfix expression

level order traversal

+ * E * D / C A B

backSlide7

Binary Search Trees

Key property

Value at node

Smaller values in left

subtreeLarger values in right subtreeExample

X

> Y

X <

Z

Y

X

Z

backSlide8

Tree traversal

Two types of tree traversal are;

Recursive

Non recursive

backSlide9

Preorder: node, left, right

Inorder

: left, node, right

Postorder

: left, right, nodeRecursive traversal

backSlide10

In this stack is used to implement the non recursive traversal.

All nodes first put into the stack and then each node is processed according to traversal.

Non recursive traversal

backSlide11

Binary Search Trees

Binary search trees

Not a binary search tree

5

10

30

2

25

45

5

10

45

2

25

30

5

10

30

2

25

45Slide12

Example Binary

Searches

Find (root, 25 )

5

10

30

2

25

45

5

10

30

2

25

45

10 < 25, right

30 > 25, left

25 = 25, found

5 < 25, right

45 > 25, left

30 > 25, left

10 < 25, right

25 = 25, foundSlide13

Types of Binary Trees

Degenerate – only one child

Complete – always two children

Balanced – “mostly” two children

more formal definitions exist, above are intuitive ideas

Degenerate binary tree

Balanced binary tree

Complete binary tree

backSlide14

Threaded Binary Trees

Two many null pointers in current representation

of binary trees

n: number of nodes

number of non-null links: n-1 total links: 2n

null links: 2n-(n-1)=n+1

Replace these null pointers with some useful “threads”.

backSlide15

Pre-order traversal while duplicating nodes and values can make a complete duplicate of a

binary tree

. It can also be used to make a prefix expression (

Polish notation

) from expression trees: traverse the expression tree pre-orderly.In-order traversal is very commonly used on binary search trees because it returns values from the underlying set in order, according to the comparator that set up the binary search tree (hence the name).

Post-order traversal while deleting or freeing nodes and values can delete or free an entire binary tree. It can also generate a postfix

representation of a binary tree.

Applications

backSlide16

Thank You