non linear data structure -introduction of tree

Tree
A tree is defined as a finite set of one or more
nodes such that [a] There is a specially
designated node called the root and
[b] The rest of the nodes could be partitioned
into t disjoint sets (t >0) each set representing
a tree Ti, i=1,2, . . . t known as sub tree of the
tree.
2

Tree
A node in the definition of the tree
represents an item of information,
and the links between the nodes
termed as branches, represent an
association between the items of
information.
3

A
B C D E
F G H I J K
L
Level 1
Level 2
Level 3
Level 4
4

Tree
 Definition of Tree emphasizes on the aspect of
[a] Connectedness, and
[b] Absence of closed loops
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Basic terminologies
degree of the node
 leaf nodes or terminal nodes
non terminal nodes
 children
 siblings
ancestors
degree of a tree
hierarchical structure
height or depth of a tree
 forest
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Tree Terminology
 A tree consists of a collection of elements or nodes, with
each node linked to its successors
 The node at the top of a tree is called its root
 The links from a node to its successors are called
branches
 The successors of a node are called its children
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Tree Terminology (continued)
 Each node in a tree has exactly one parent except for
the root node, which has no parent
 Nodes that have the same parent are siblings
 A node that has no children is called a leaf node
 A generalization of the parent-child relationship is the
ancestor-descendent relationship
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 The predecessor of a node is called its parent
 A sub tree of a node is a tree whose root is a child of
that node
 The level of a node is a measure of its distance from
the root
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 Node: stores the actual data and links to other nodes
 Parent: immediate predecessor of a node
 Root: specially designated node which has no parent
 Child: immediate successor of a node.
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Tree Terminology(continued)
 Leaf: node without any child
 Level: rank of the hierarchy and root node has level
zero(0). Node at level i has the level i+1 for its child
and i-1 for its parent. This is true for all nodes except
the root
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 Height (depth): Maximum number of nodes possible
in a path starting from root node to leaf node. Height
of a tree given by h = lmax, lmax is the maximum level of
the tree.
 Degree of node maximum number of children
possible for a node
 Siblings  nodes having the same parent
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Tree Terminology
 Ancestor of a Node: Those nodes that occur on the
path from the root to the given node
 Degree of a Tree: Maximum degree of the node in the
tree
 Forest : A set of Zero or more Disjoint trees.
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A
B C D E
F G H I J K
L
Level 1
Level 2
Level 3
Level 4
Degree of the tree = 4 (
Max degree of A)
Height of the tree = 4 (Max
level)
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Representation of a tree
 List Representation
(A (B(F,G,H), C, D(I), E(J,K(L))) ) for the tree
Considered in the Example
15
• Linked List Representation

DATA LINK 1 LINK 2 … LINK n
(a) General node structure
T
A
B
C D E
F K
G H I
L
J
(b) Linked list representation of the tree
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Binary Trees
A binary tree T is defined as a finite set of elements
called nodes such that
[a] T is empty (Called the Null tree or Empty tree) or
[b] T contains a distinguished node R called the root of T
and the remaining nodes of T form an ordered pair of
disjoint binary trees T1 and T2
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Binary Trees
 A binary tree has the characteristic of all nodes
having at most two branches, that is, all nodes have a
degree of at most 2.
A binary tree can therefore be empty or consist of a
root node and two disjoint binary trees termed left
subtree and right subtree.
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A
G
C
D
B
E F
Level 1
Level 2
Level 3
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Important observations regarding binary trees:
 The maximum number of nodes on level i of a
binary tree is 2i-1, i>1
 The maximum number of nodes in a binary tree
of height h is 2h-1, h>1
 For any non empty binary tree, if to is the
number of terminal nodes and t2 is the number
of nodes of degree 2, then to=t2+1
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A binary tree of height h which has all its permissible
maximum number of nodes viz., 2h-1 intact is known as a
full binary tree of height h.
21
A
G
C
D
B
E F
1
2 3
4 5
6
7

A binary tree with n’ nodes and height h is complete
if its nodes correspond to the nodes which are
numbered 1 to n (n’ n) in a full binary tree of
height h.
22
A
C
D
B
1
E F
2
3
4 5 6
Height of a complete
binary tree with n given
by
log ( 1) 2 h  n 

A complete binary tree obeys the following
properties with regard to its node numbering:
[a] If a parent node has a number i then its left
child has the number 2i (2i < n). If 2i > n then i
has no left child.
[b] If a parent node has a number i, then its right
child has the number 2i+1 (2i + 1 <n). If 2i + 1 > n
then i has no right child.
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A complete binary tree obeys the following
properties with regard to its node numbering:
[c] If a child node (left or right) has a number i then
the parent node has the number i /2 if i 1. If i
=1 then i is the root and hence has no parent.
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A binary tree which is dominated solely by left
child nodes or right child nodes is called a skewed
binary tree or more specifically left skewed
binary tree or right skewed binary tree
respectively.
a
b
c
d
n
o
m
Left skewed Right skewed
p
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Extended Binary Tree: 2-Tree
A binary tree T is said to be 2-Tree or an extended binary
tree if each node N has either 0 or 2 children.
Nodes with 2 children are called internal nodes and the
nodes with 0 children are called external nodes.
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Representation of Binary Tree
Binary tree can be represented by means of
[a] Array
[b] linked list
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Representation Of Binary Trees
Array Representation
Sequential representation of a
tree with depth d will require
an array with approx 2d + 1
elements
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2
4 5
10
1
a
c
b
e
d
f
11
1 2 3 4 5 6 7 8 9 10 11
a b c d e f

Linked representation
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LCHILD DATA RCHILD
a
b
c d
T
e f

 Observation regarding the linked representation of
Binary Tree
[a] If a binary tree has n nodes then the number of
pointers used in its linked representation is 2 * n
[b] The number of null pointers used in the linked
representation of a binary tree with n nodes is n + 1
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Traversing Binary Tree
Three ways of traversing the binary tree T with root R
Preorder
[a] Process the root R
[b] Traverse the left sub-tree of R in preorder
[c] Traverse the right sub-tree of R in preorder
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a. k. a node-left-right traversal (NLR)

In-order
[a] Traverse the left sub-tree of R in in-order
[b] Process the root R
[c] Traverse the right sub-tree of R in in-order
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a. k. a left-node-right traversal (LNR)

Post-order
[a] Traverse the left sub-tree of R in post-order
[b] Traverse the right sub-tree of R in post-order
[c] Process the root R
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a. k. a left-right-node traversal (LRN)

Illustrations for Traversals
 Assume: visiting a node
is printing its label
 Preorder:
1 3 5 4 6 7 8 9 10 11 12
 Inorder:
4 5 6 3 1 8 7 9 11 10 12
 Postorder:
4 6 5 3 8 11 12 10 9 7 1
8 9
10
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1
3
11
5
4 6
7
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Illustrations for Traversals (Contd.)
 Assume: visiting a node
is printing its data
 Preorder: 15 8 2 6 3 7
11 10 12 14 20 27 22 30
 Inorder: 2 3 6 7 8 10 11
12 14 15 20 22 27 30
 Postorder: 3 7 6 2 10 14
12 11 8 22 30 27 20 15
35
6
15
8
2
3 7
11
10
14
12
20
27
22 30

Formulation of Binary tree from
Its traversal
1. If preorder is given=>First node is the root
If postorder is given=>Last node is the root
2. Once the root node is identified ,all nodes in the left
subtrees and right subtrees of the root node can be
identified.
3. Same technique can be applied repeatedly to form
subtrees
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4.Two traversals are essential out of which one should
inorder, another may be preorder or postorder
5. But we can’t form a binary tree if only preorder and
postorder has given.
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Example: For Given Inorder and
Preorder
Inorder: D B H E A I F J F CG
Preorder: A B D E H C F I J G
Now root is A
Left subtree: D B H E
Right subtree: I F J C G
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continues.
A
In:D B H E I F J C G
Pre:B D E H C F I J G
D H E I F J G
E H F I J
I J
H
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Example: For Given Inorder and
Postorder
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Inorder: n1,n2, n3, n4, n5, n6, n7, n8,
n9
Postorder: n1,n3, n5, n4, n2, n8, n7,
n9, n6
So here n6 is the root

 Reference:
 Data structure using c by Rina Thareja
 Data structure using c by Trembly Sorenson
 http://en.wikipedia.org/wiki/datastructure
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non linear data structure -introduction of tree

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