Prepare for Binary Tree Data Structure Interview with iQwizz | Difficulty Level: Advance | Rating: 4.8

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Question 1

What type of tree rotation is required to rebalance the following AVL tree after inserting the value '1'? (Assume standard AVL tree properties) 4 /
2 5 / 1

Right-Left Rotation
Left Rotation
Left-Right Rotation
Right Rotation

Question 2

What is the time complexity of the most efficient algorithm to convert a sorted array to a balanced Binary Search Tree?

O(n log n)
O(log n)
O(n)
O(1)

Question 3

What is the worst-case time complexity for searching for a specific value in a perfectly balanced BST?

O(1)
O(n log n)
O(log n)
O(n)

Question 4

What is the output of this Python code that performs a Level Order Traversal (BFS) on a Binary Tree?

from collections import deque

class Node:
    def __init__(self, data):
        self.data = data
        self.left = None
        self.right = None

def level_order(root):
    if root is None:
        return
    nodes = deque([root])
    while(len(nodes) > 0):
        curr = nodes.popleft()
        print(curr.data, end=' ')
        if curr.left:
            nodes.append(curr.left)
        if curr.right:
            nodes.append(curr.right)

# Binary Tree Construction
root = Node(1)
root.left = Node(2)
root.right = Node(3)
root.left.left = Node(4)
root.left.right = Node(5)

level_order(root)

4 5 2 3 1
4 2 5 1 3
1 2 3 4 5
1 2 4 5 3

Question 5

Which of the following statements is FALSE about a Balanced Binary Tree?

It aims to keep the height of the tree as minimal as possible.
AVL and Red-Black trees are examples of self-balancing binary search trees.
All Balanced Binary Trees strictly enforce a height difference of at most 1 between the left and right subtrees.
It ensures that search, insertion, and deletion operations have a time complexity of O(log n).

Question 6

What is the primary advantage of using a Segment Tree over a naive approach for range queries on an array?

Segment Trees provide logarithmic time complexity for both range queries and updates.
Segment Trees reduce the space complexity compared to the original array.
Segment Trees are easier to implement than the naive approach, especially for large arrays.
Segment Trees offer faster updates but slower queries.

Question 7

Which of the following is a key property of a Red-Black Tree that ensures its balance?

Every path from the root to a leaf node has the same number of black nodes.
A red node cannot have a red child.
The root node is always black.
All of the above.

Question 8

Consider a Binary Search Tree (BST). What is the time complexity of finding the LCA of two nodes in the BEST-CASE scenario?

O(n)
O(n log n)
O(log n)
O(1)

Question 9

What is the primary advantage of using a Fenwick tree over a segment tree for range sum queries?

Fenwick trees support a wider range of queries
Fenwick trees have faster update operations
Fenwick trees are easier to implement
Fenwick trees use less memory

Question 10

In a Perfect Binary Tree with height 'h', what is the maximum number of nodes it can have?

h^2
2^(h+1) - 1
2h + 1
2^h - 1

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Question 1

What type of tree rotation is required to rebalance the following AVL tree after inserting the value '1'? (Assume standard AVL tree properties) 4 /
2 5 / 1

Right-Left Rotation
Left Rotation
Left-Right Rotation
Right Rotation

Question 2

What is the time complexity of the most efficient algorithm to convert a sorted array to a balanced Binary Search Tree?

O(n log n)
O(log n)
O(n)
O(1)

Question 3

What is the worst-case time complexity for searching for a specific value in a perfectly balanced BST?

O(1)
O(n log n)
O(log n)
O(n)

Question 4

What is the output of this Python code that performs a Level Order Traversal (BFS) on a Binary Tree?

from collections import deque

class Node:
    def __init__(self, data):
        self.data = data
        self.left = None
        self.right = None

def level_order(root):
    if root is None:
        return
    nodes = deque([root])
    while(len(nodes) > 0):
        curr = nodes.popleft()
        print(curr.data, end=' ')
        if curr.left:
            nodes.append(curr.left)
        if curr.right:
            nodes.append(curr.right)

# Binary Tree Construction
root = Node(1)
root.left = Node(2)
root.right = Node(3)
root.left.left = Node(4)
root.left.right = Node(5)

level_order(root)

4 5 2 3 1
4 2 5 1 3
1 2 3 4 5
1 2 4 5 3

Question 5

Which of the following statements is FALSE about a Balanced Binary Tree?

It aims to keep the height of the tree as minimal as possible.
AVL and Red-Black trees are examples of self-balancing binary search trees.
All Balanced Binary Trees strictly enforce a height difference of at most 1 between the left and right subtrees.
It ensures that search, insertion, and deletion operations have a time complexity of O(log n).

Question 6

What is the primary advantage of using a Segment Tree over a naive approach for range queries on an array?

Segment Trees provide logarithmic time complexity for both range queries and updates.
Segment Trees reduce the space complexity compared to the original array.
Segment Trees are easier to implement than the naive approach, especially for large arrays.
Segment Trees offer faster updates but slower queries.

Question 7

Which of the following is a key property of a Red-Black Tree that ensures its balance?

Every path from the root to a leaf node has the same number of black nodes.
A red node cannot have a red child.
The root node is always black.
All of the above.

Question 8

Consider a Binary Search Tree (BST). What is the time complexity of finding the LCA of two nodes in the BEST-CASE scenario?

O(n)
O(n log n)
O(log n)
O(1)

Question 9

What is the primary advantage of using a Fenwick tree over a segment tree for range sum queries?

Fenwick trees support a wider range of queries
Fenwick trees have faster update operations
Fenwick trees are easier to implement
Fenwick trees use less memory

Question 10

In a Perfect Binary Tree with height 'h', what is the maximum number of nodes it can have?

h^2
2^(h+1) - 1
2h + 1
2^h - 1

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