Tree Terminology Root Leaf Height Depth Level in DSA Python - Time & Space Complexity

Time Complexity: Tree Terminology Root Leaf Height Depth Level

O(n)

Understanding Time Complexity

When working with trees, it is important to understand how the time to do tasks grows as the tree gets bigger.

We want to know how operations like finding height or depth take longer when the tree has more nodes.

Scenario Under Consideration

Analyze the time complexity of this code that finds the height of a binary tree.

def tree_height(node):
    if node is None:
        return 0
    left_height = tree_height(node.left)
    right_height = tree_height(node.right)
    return 1 + max(left_height, right_height)

This code finds the height by checking the height of left and right subtrees recursively.

Identify Repeating Operations

Look at what repeats as the function runs:

• Primary operation: Recursive calls to visit each node once.
• How many times: Once for every node in the tree.

How Execution Grows With Input

As the tree grows, the function visits every node once to find height.

Input Size (n)	Approx. Operations
10	About 10 visits
100	About 100 visits
1000	About 1000 visits

Pattern observation: Operations grow directly with the number of nodes.

Final Time Complexity

Time Complexity: O(n)

This means the time to find the height grows in a straight line with the number of nodes.

Common Mistake

[X] Wrong: "The height function only checks the longest path, so it runs faster than visiting all nodes."

[OK] Correct: The function must visit every node to be sure of the longest path, so it touches all nodes anyway.

Interview Connect

Understanding how tree operations scale helps you explain your solutions clearly and confidently in interviews.

Self-Check

"What if we changed the tree to be a linked list (all nodes have only one child)? How would the time complexity change?"

Practice

1. In a tree data structure, which node is called the root?

easy

A. A node at the lowest level

B. The topmost node with no parent

C. Any node with no children

D. A node with exactly two children

Solution

1. Step 1: Understand the root node definition

   The root node is the starting point of the tree and has no parent node above it.

2. Step 2: Compare options with definition

   The topmost node with no parent matches this definition exactly. Other options describe leaf nodes or other properties.

3. Final Answer:

   The topmost node with no parent -> Option B

4. Quick Check:

   Root = topmost node with no parent [OK]

Hint: Root is always the top node without a parent [OK]

Common Mistakes:

• Confusing root with leaf node
• Thinking root has children always
• Mixing root with internal nodes

2. Which of the following is the correct way to represent the leaf node in a tree?

easy

A. A node with no children

B. A node with exactly one child

C. The root node

D. A node with at least one child

Solution

1. Step 1: Define leaf node

   A leaf node is a node that has no children; it is at the end of a branch.

2. Step 2: Match definition with options

   A node with no children states a node with no children, which matches the leaf node definition.

3. Final Answer:

   A node with no children -> Option A

4. Quick Check:

   Leaf = node with no children [OK]

Hint: Leaf nodes have zero children [OK]

Common Mistakes:

• Thinking leaf nodes have children
• Confusing leaf with root
• Assuming leaf nodes must have one child

3. Consider the following tree structure:

       A
      / \
     B   C
    /   / \
   D   E   F

What is the height of node C?

medium

A. 0

B. 2

C. 3

D. 1

Solution

1. Step 1: Understand height of a node

   Height is the number of edges on the longest path from the node down to a leaf.

2. Step 2: Calculate height of node C

   Node C has children E and F, both leaves with height 0. So height of C = 1 + max(0,0) = 1.

3. Step 3: Verify options

   1 says 1, but height counts edges down, so height is 1. 2 says 2, which is incorrect. 0 is 0, which is leaf height.

4. Final Answer:

   1 -> Option D

5. Quick Check:

   Height of C = 1 edge to leaf [OK]

Hint: Height counts edges down to farthest leaf [OK]

Common Mistakes:

• Confusing height with depth
• Counting nodes instead of edges
• Assuming leaf height is 1

4. Given the tree below:

       X
      / \
     Y   Z
    / 
   W  

What is the depth of node W?
Note: Depth is the number of edges from the root to the node.

medium

A. 2

B. 1

C. 0

D. 3

Solution

1. Step 1: Understand depth definition

   Depth is the number of edges from the root node to the target node.

2. Step 2: Trace path from root to W

   Path: X (root) -> Y -> W. Number of edges = 2.

3. Final Answer:

   2 -> Option A

4. Quick Check:

   Depth of W = 2 edges from root [OK]

Hint: Count edges from root to node for depth [OK]

Common Mistakes:

• Counting nodes instead of edges
• Confusing depth with height
• Starting count from 1 instead of 0

5. In a tree, the level of a node is defined as its depth plus one. Given the tree:

        M
       / \
      N   O
     / \
    P   Q

What is the level of node Q?

hard

A. 1

B. 2

C. 3

D. 4

Solution

1. Step 1: Find depth of node Q

   Path from root M to Q is M -> N -> Q, which has 2 edges, so depth = 2.

2. Step 2: Calculate level using formula

   Level = depth + 1 = 2 + 1 = 3.

3. Final Answer:

   3 -> Option C

4. Quick Check:

   Level = depth + 1 = 3 [OK]

Hint: Level = depth + 1 always [OK]

Common Mistakes:

• Using depth as level directly
• Counting nodes incorrectly
• Confusing level with height