Binary Tree
• A data structure whose nodes contain two pointer fields.
• One or both pointers can have the value NULL.
• Each node in a binary tree can have 0, 1, or 2 successor
nodes.
Root node
FOX
Left subtree
Right subtree
HEN
DOG
CAT
ELF
HAT
HOG
Binary Tree
• Root node => the first node in a binary tree
• left subtree => the part of a tree pointed to by the left
pointer of the root node.
• right subtree => the part of a tree pointed to by the right
pointer of the root node
Root node
FOX
Left subtree
Leaf
node
Right subtree
HEN
DOG
CAT
ELF
HAT
HOG
siblings
Binary Search Tree
• A particular kind of binary tree.
• A tree structure that stores data in such a way that they
can be retrieved very efficiently.
• Every item stored in a binary search tree has a unique
key.
• A binary search tree is either empty or has the property
that the item in its root has a larger key than each item in
its left subtree and a smaller key than each item in its
right subtree.
• Its left and right subtrees must be binary search trees.
• The string stored in every node is alphabetically larger
than all strings in its left subtree and alphabetically
smaller than all strings in its right subtree.
•
•
•
•
Binary search Tree
Root node =>35
Root of left subtree => 25
Root of right subtree => 40
The number stored in every node is larger than all
numbers in its left subtree and smaller than all numbers
Root node
in right subtree.
35
Left subtree
Right subtree
40
25
15
30
38
45
siblings
Searching a Binary Search Tree
Algorithm:
1 if the tree is empty
2 The target key is not in the tree.
else if the target key is in the root item
3 The target key is found in the root item.
else if target is smaller than the root’s key
4 Search the left subtree.
else
5 Search the right subtree.
Building a Binary Search Tree
• Before we can retrieve an item from a binary search tree,
we have to build the tree.
• Building a binary search tree requires that
- we scan a collection of data items that is no
particular order and insert each one individually
- make sure that the expanded tree is a binary search
tree.
• A binary tree builds from the root node down, so we
have to store the first data item in the root node.
• To store each subsequent data item, we have to find out
the appropriate node to be its parent, attach a new node
to the parent, and then store that data item in the new
node.
Algorithm for Insertion in a Binary Search Tree
1 if the tree is empty
2 Insert the new item in the tree’s root node.
else if the root’s key matches the new item’s key
3 Skip insertion - duplicate key.
else if the new item’s key is smaller than the root’s key
4 Insert the new item in the root’s left subtree.
else
5 Insert the new item in the root’s right subtree.
Building a Binary Search Tree
• Builds a tree from the list of keys: 40, 20, 10, 50, 65, 45,
30.
root
40
50
20
10
30
45
65
Structure Types for a Binary Tree
typedef struct tree_node_s
{
int key;
struct tree_node_s *leftp, *rightp;
} tree_node_t;
Function tree_insert
tree_node_t *tree_insert (tree_node_t *rootp, int new_key)
{
if (rootp == NULL) // simple case 1 - empty tree
{
rootp = (tree_node_t *) malloc(sizeof(tree_node_t));
rootp->key = new_key;
rootp->leftp = NULL;
rootp->rightp = NULL;
}
else if (new_key == root->key) // simple case 2, duplicate key, no insertion
else if (new_key < rootp->key) // insert in left subtree
rootp->leftp = tree_insert(rootp->leftp, new_key);
else
// insert in right subtree
rootp->rightp = tree_insert (rootp->rightp, new_key);
return (rootp);
}
Displaying a Binary Search Tree
• To display the contents of a binary search tree so that its
items are listed in order by key value, use the following
algorithm:
1 if the tree is not empty
2 Display left subtree.
3 Display root item.
4 Display right subtree.
• Because the algorithm displays the items in order by key
value, this algorithm is called an inorder traversal.
Display the Left Subtree of 40
• Trace of Tree Display Algorithm:
Display left subtree of node 40.
root
Display left subtree of node 20.
40
Display left subtree of node 10.
Tree is empty-return from
50
20
displaying left subtree of node 10.
Display item with key 10.
65 Display right subtree of node 10.
10
45
30
Tree is empty - return from
displaying right subtree of node 10.
Display right subtree of node 30.
Return from displaying left subtree
Tree is empty-return from displaying
of node 20.
right subtree of node 30.
Display item with key 20.
Return from displaying right subtree
Display right subtree of node 20.
of node 20.
Display left subtree of node 30.
Return from displaying left subtree of
Tree is empty- return from displaying
node 40.
left subtree of node 30.
Display item with key 40.
Display item with key 30.
………………………..
Programming Error with heap Management
• Problems with heap management can cause run-time
errors.
• If your program gets struck in an infinite loop while
creating a dynamic data structure, your program can
consume all memory cells on the storage heap.
• This situation can result in a heap overflow or stack
overflow run-time error.
• Make sure your program does not attempt to reference a
list node after the node is returned to the heap. You have
to be careful to return a storage block to the heap before
losing all pointers to it.