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

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Question 1

What is the key invariant property of a Binary Search Tree (BST) that differentiates it from a regular Binary Tree?

Every node has at most two children.
The tree is always complete.
The height of the tree is always balanced.
The left subtree of a node contains only values less than the node's value, and the right subtree contains only values greater than the node's value.

Question 2

What is the maximum number of nodes in a binary tree of height 'h'?

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

Question 3

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

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

Question 4

You need to transmit a large file containing English text. Using a Huffman tree, which of these characters is likely to have the shortest codeword?

Question 5

You are tasked with determining if two binary trees are mirrors of each other. Which traversal method pair can be used to efficiently compare the trees?

Level Order of both trees
Preorder of one tree with Postorder of the other
Preorder of one tree with Inorder of the other
Inorder of both trees

Question 6

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

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

Question 7

You want to print the nodes of a binary tree in a way that nodes at the same level are printed together, from left to right. Which traversal method achieves this?

Level Order Traversal
Inorder Traversal
Postorder Traversal
Preorder Traversal

Question 8

What is the primary advantage of using a Red-Black Tree over an AVL Tree?

Red-Black Trees have faster insertion and deletion operations in practice.
Red-Black Trees are simpler to implement.
Red-Black Trees are always more balanced than AVL Trees.
Red-Black Trees use less memory.

Question 9

Analyze this C++ function designed to find the lowest common ancestor (LCA) in a Binary Search Tree (BST). Is it correctly implemented?

Node* lca(Node* root, int n1, int n2) {
    if (root == NULL) return NULL;

    if (root->data > n1 && root->data > n2)
        return lca(root->left, n1, n2);

    if (root->data < n1 && root->data < n2)
        return lca(root->right, n1, n2);

    return root;
}

Yes, the code efficiently finds the LCA in a BST.
No, the code doesn't handle the case where one or both nodes are not present in the BST.

Question 10

Examine this Python code attempting to find the diameter of a Binary Tree. Is it implemented correctly?

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

def diameter(root):
    if root is None:
        return 0
    lheight = height(root.left)
    rheight = height(root.right)
    return max(lheight + rheight + 1, max(diameter(root.left), diameter(root.right)))

def height(node):
    if node is None:
        return 0
    return 1 + max(height(node.left), height(node.right))

Yes, the code accurately determines the diameter of the binary tree.
No, the code has a logical error in calculating the diameter.

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Question 1

What is the key invariant property of a Binary Search Tree (BST) that differentiates it from a regular Binary Tree?

Every node has at most two children.
The tree is always complete.
The height of the tree is always balanced.
The left subtree of a node contains only values less than the node's value, and the right subtree contains only values greater than the node's value.

Question 2

What is the maximum number of nodes in a binary tree of height 'h'?

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

Question 3

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

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

Question 4

You need to transmit a large file containing English text. Using a Huffman tree, which of these characters is likely to have the shortest codeword?

Question 5

You are tasked with determining if two binary trees are mirrors of each other. Which traversal method pair can be used to efficiently compare the trees?

Level Order of both trees
Preorder of one tree with Postorder of the other
Preorder of one tree with Inorder of the other
Inorder of both trees

Question 6

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

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

Question 7

You want to print the nodes of a binary tree in a way that nodes at the same level are printed together, from left to right. Which traversal method achieves this?

Level Order Traversal
Inorder Traversal
Postorder Traversal
Preorder Traversal

Question 8

What is the primary advantage of using a Red-Black Tree over an AVL Tree?

Red-Black Trees have faster insertion and deletion operations in practice.
Red-Black Trees are simpler to implement.
Red-Black Trees are always more balanced than AVL Trees.
Red-Black Trees use less memory.

Question 9

Analyze this C++ function designed to find the lowest common ancestor (LCA) in a Binary Search Tree (BST). Is it correctly implemented?

Node* lca(Node* root, int n1, int n2) {
    if (root == NULL) return NULL;

    if (root->data > n1 && root->data > n2)
        return lca(root->left, n1, n2);

    if (root->data < n1 && root->data < n2)
        return lca(root->right, n1, n2);

    return root;
}

Yes, the code efficiently finds the LCA in a BST.
No, the code doesn't handle the case where one or both nodes are not present in the BST.

Question 10

Examine this Python code attempting to find the diameter of a Binary Tree. Is it implemented correctly?

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

def diameter(root):
    if root is None:
        return 0
    lheight = height(root.left)
    rheight = height(root.right)
    return max(lheight + rheight + 1, max(diameter(root.left), diameter(root.right)))

def height(node):
    if node is None:
        return 0
    return 1 + max(height(node.left), height(node.right))

Yes, the code accurately determines the diameter of the binary tree.
No, the code has a logical error in calculating the diameter.

Binary Tree Data Structure Questions

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