Download Binary Trees

Chapter 10
– Binary Trees
Tree Structures (3 slides)
Tree Node Level and Path Len.
(5 slides)
Binary Tree Definition
Selected Samples / Binary Trees
Binary Tree Nodes
Binary Search Trees
Locating Data in a Tree
Removing a Binary Tree Node
stree ADT (4 slides)
Using Binary Search Trees
- Removing Duplicates
Update Operations (3 slides)
Removing an Item From a
Binary Tree (7 slides)
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Main Index
Summary Slides (5 slides)
Contents
Tree Structures
President-CEO
Production
Manager
Personnel
Manager
Purchasing
Supervisor
Warehouse
Supervisor
Sales
Manager
Shipping
Supervisor
HIERARCHICAL TREE STRUCTURE
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Tree Structures
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*
a
/
c
d
BINARY EXPRES S ION TREE FOR "a*b
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b
Contents
+ (c-d) / e"
Tree Structures
A
B
C
E
F
D
G
(b)
I
J
(a)
A GENERAL TREE
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H
Tree Node Level and Path
Length
Level: 0
A
B
C
E
G
5
D
Level: 1
Level: 2
F
H
Level: 3
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Tree Node Level and Path
Length – Depth Discussion
A
B
C
D
H
E
I
F
J
Complete Tree (Depth 3)
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G
Tree Node Level and Path
Length – Depth Discussion
A
B
D
C
E
F
Complete Tree (Depth 2)
Full with all possible nodes
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G
Tree Node Level and Path
Length – Depth Discussion
A
B
D
H
C
E
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Non-Complete Tree (Depth 3)
Level 2 is missing nodes
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Tree Node Level and Path
Length – Depth Discussion
A
B
D
H
C
E
F
G
K
I
Non-CompleteTree (Depth 3)
Nodes at level 3 do not occurpy leftmost positions
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
Binary Tree Definition
A binary tree T is a finite set of nodes with one
of the following properties:
–
–
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(a) T is a tree if the set of nodes is empty.
(An empty tree is a tree.)
(b) The set consists of a root, R, and exactly two
distinct binary trees, the left subtree TL and the
right subtreeTR. The nodes in T consist of node
R and all the nodes in TL and TR.
Main Index
Contents
Selected Samples of Binary
Trees
A
A
B
B
C
C
D
E
F
G
D
H
E
I
Tree B
Size 5 Depth 4
Tree A
Size 9 Depth 3
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A
Binary Tree Nodes
B
C
D
E
F
H
G
left
A
right
Abstract Tree Model
left
B
right
left
left
G
left
D
right
left
E
right
left
Main Index
right
right
Tree Node Model
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C
Contents
left
H
right
F
right
Binary Search Trees
25
30
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37
50
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Binary Search Tree 1
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Binary Search Tree 3
Binary Search Tree 2
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Current Node
Root = 50
Action -LOCATING DATA IN A TREECompare item = 37 and 50
37 < 50, move to the left subtree
Compare item = 37 and 30
37 > 30, move to the right subtree
Compare item = 37 and 35
37 > 35, move to the right subtree
Compare item = 37 and 37. Item
Node = 30
Node = 35
Node = 37
found.
50
30
55
25
10
35
32
53
62
37
15
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Contents
Removing a Binary Search Tree
Node
25
//
\\
10
37
15
65
30
Delete node 25
30
37
10
10
65
15
65
15
30
Good Solution
Bad Solution: 30 is out of place
(b)
(a)
15
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CLASS stree
Constructors
“d_stree.h”
stree();
Create an empty search tree.
stree(T *first, T *last);
Create a search tree with the elements from the
pointer range [first, last).
CLASS stree
Opertions
“d_stree.h”
void displayTree(int maxCharacters);
Display the search tree. The maximum number of
characters needed to output a node value is
maxCharacters.
bool empty();
Return true if the tree is empty and false otherwise.
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CLASS stree
Opertions
“d_stree.h”
int erase(const T& item);
Search the tree and remove item, if it is present;
otherwise, take no action. Return the number of
elements removed.
Postcondition: If item is located in the tree, the size
of the tree decreases by 1.
void erase(iterator pos);
Erase the item pointed to the iterator pos.
Precondition: The tree is not empty and pos points
to an item in the tree. If the iterator is invalid, the
function throws the referenceError exception.
Postcondition: The tree size decreases by 1.
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CLASS stree
Opertions
“d_stree.h”
void erase(iterator first, iterator last);
Remove all items in the iterator range [first, last).
Precondition: The tree is not empty. If empty, the
function throws the underflowError exception.
Postcondition: The size of the tree decreases by the
number of items in the range.
iterator find(const T& item);
Search the tree by comparing item with the data
values in a path of nodes from the root of the tree. If a
match occurs, return an iterator pointing to the
matching value in the tree. If item is not in the tree,
return the iterator value end().
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CLASS stree
Opertions
“d_stree.h”
Piar<iterator, bool> insert(const T& item);
If item is not in the tree, insert it and return an iteratorbool pair where the iterator is the location of the
newelement and the Boolean value is true. If item is
already in the tree, return the pair where the iterator
locates the existing item and the Boolean value is
false.
Postcondition: The size of the tree is increased by 1
if item is not present in the tree.
int size();
Return the number of elements in the tree.
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Using Binary Search Trees
Application: Removing Duplicates
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v
2
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3
7 3 2 5 3 2 9 3
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Contents
v
2 3 5 7 9
Update Operations: 1st of 3 steps
1)-
The function begins at the root node and compares item 32
with the root value 25. Since 32 > 25, we traverse the right
subtree and look at node 35.
parent
25
20
t
35
12
40
(a)
Step 1: Compare 32 and 25.
Traverse the right subtree.
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Update Operations: 2nd of 3 steps
2)-
Considering 35 to be the root of its own subtree, we compare
item 32 with 35 and traverse the left subtree of 35.
25
20
12
40
t
(b)
Step 2: Compare 32 and 35.
Traverse the left subtree.
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parent
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Update Operations: 3rd of 3 steps
1)-
Create a leaf node with data value 32. Insert the new node
as the left child of node 35.
newNode = getSTNode(item,NULL,NULL,parent);
parent->left = newNode;
25
20
12
32
(c)
Step 3: Insert 32 as left child
of parent 35
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parent
35
Contents
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Removing an Item From a
Binary Tree
Before
After
40
40
30
P
D
25
10
35
26
30
65
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P
35
26
50
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No replacement is necessary.
pNodePtr->left is NULL
Delete leaf node 10.
pNodePtr->left is dNode
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25
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Removing an Item From a
Binary Tree
Before
After
40
P
30
25
10
40
65
D
26
33
29
35
R
50
P
30
25
10
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R
33
50
34
26
34
29
28
28
Delete node 35 with only a left child:
Node R is the left child.
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Attach node R to the parent.
Contents
Removing an Item From a
Binary Tree
Before
After
40
40
30
P
10
65
25
D
35
26
R
P
50
33
29
30
10
25
R
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34
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35
29
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34
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Delete node 26 with only a right child:
Node R is the right child.
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Attach node R to the parent.
Contents
Removing an Item From a
Binary Tree
40
40
30
65
25
10
35
26
50
25
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65
35
26
10
34
34
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Delete node 30 with two children.
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Main Index
Orphaned subtrees.
Contents
Removing an Item From a
Binary Tree
Before replacing D by R
After replacing D by R
40
P
pNodePtr
30
40
65
P
30
pOfRNodePtr = dNodePtr
25
D
35
26
10
R
26
29
35
R
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34
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28
R
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10
rNodePtr
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50
Removing an Item From a
Binary Tree
Before unlinking R
P
pNodePtr
40
dNodePtr
35
R
26
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rNodePtr
26
10
R
34
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D
30
65
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pOfRNodePtr
rNodePtr
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29
40
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R
25
10
P
pNodePtr
D
30
After unlinking R
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35
29
34
50
pOfRNodePtr
Removing an Item From a
Binary Tree
Before replacing D by R
After replacing D by R
P
pNodePtr
P
pNodePtr
40
40
R
R
D
30
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rNodePtr
26
10
65
35
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rNodePtr
10
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Contents
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Summary Slide 1
§- trees
- hierarchical structures that place elements in
nodes along branches that originate from a root.
- Nodes in a tree are subdivided into levels in which
the topmost level holds the root node.
§- Any node in a tree may have multiple successors at
the next level. Hence a tree is a non-linear structure.
- Tree terminology with which you should be
familiar:
parent | child | descendents | leaf node | interior
node | subtree.
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Summary Slide 2
§- Binary Trees
- Most effective as a storage structure if it has high
density
§- ie: data are located on relatively short paths from the
root.
§- A complete binary tree has the highest possible
density
- an n-node complete binary tree has depth
int(log2n).
- At the other extreme, a degenerate binary tree is
equivalent to a linked list and exhibits O(n) access
times.
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Summary Slide 3
§- Traversing Through a Tree
- There are six simple recursive algorithms for tree
traversal.
- The most commonly used ones are:
1)inorder (LNR)
2)postorder (LRN)
3)preorder (NLR).
- Another technique is to move left to right from
level to level.
§- This algorithm is iterative, and its implementation
involves using a queue.
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Summary Slide 4
§- A binary search tree stores data by
value instead of position
- It is an example of an associative container.
§- The simple rules
“== return”
“< go left”
“> go right”
until finding a NULL subtree make it easy to build a
binary search tree that does not allow duplicate
values.
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Summary Slide 5
§- The insertion algorithm can be used to define the
path to locate a data value in the tree.
§- The removal of an item from a binary search tree is
more difficult and involves finding a replacement
node among the remaining values.
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