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Assignment Type | Turnaround Time | Price (USD) |
---|---|---|
Array and Linked List Implementation | 24 Hours | $30 |
Binary Trees and Binary Search Trees | 48 Hours | $40 |
Graph Algorithms and Traversals | 3 Days | $50 |
Sorting Algorithms (Quick Sort, Merge Sort, etc.) | 5 Days | $45 |
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- Key Role of Algorithms in Computer Science Curriculum
- Data Structures and Analysis of Algorithms Assignment Help
- Why Students Should Get Expert Help with Data Structures and Analysis of Algorithms Assignments?
- Implementation of Binary Search Tree (BST)
- Advantages Offered by Our Data Structures and Analysis of Algorithms Assignment Help Service
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Implementation of Binary Search Tree (BST)
class TreeNode:
def __init__(self, key):
self.left = None
self.right = None
self.val = key
def insert(root, key):
if root is None:
return TreeNode(key)
else:
if root.val < key:
root.right = insert(root.right, key)
else:
root.left = insert(root.left, key)
return root
def inorder_traversal(root):
if root:
inorder_traversal(root.left)
print(root.val)
inorder_traversal(root.right)
# Example usage:
if __name__ == "__main__":
r = TreeNode(50)
r = insert(r, 30)
r = insert(r, 20)
r = insert(r, 40)
r = insert(r, 70)
r = insert(r, 60)
r = insert(r, 80)
print("Inorder traversal of the BST is:")
inorder_traversal(r)
Explanation:
- TreeNode Class: Defines the structure of a tree node with attributes left and right for left and right children, and val for the node's value.
- Insert Function: Recursively inserts a new key into the BST while maintaining the property that all nodes in the left subtree are less than the root, and all nodes in the right subtree are greater.
- Inorder Traversal Function: Performs an inorder traversal of the BST, which visits nodes in ascending order (left subtree, root, right subtree).
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