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

Time Complexity: Tree Terminology Root Leaf Height Depth Level

O(n)

Understanding Time Complexity

We want to understand how the time to work with a tree changes as the tree grows.

Specifically, how operations related to root, leaf, height, depth, and level scale with tree size.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

public class TreeNode {
    public int Value;
    public TreeNode Left, Right;
    public TreeNode(int val) { Value = val; }
}

int GetHeight(TreeNode node) {
    if (node == null) return 0;
    return 1 + Math.Max(GetHeight(node.Left), GetHeight(node.Right));
}
    

This code calculates the height of a binary tree by checking the longest path from the root to any leaf.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Recursive calls visiting each node once.
• How many times: Once per node in the tree.

How Execution Grows With Input

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

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

Pattern observation: The number of operations grows directly with the number of nodes.

Final Time Complexity

Time Complexity: O(n)

This means the time to find the height grows linearly with the number of nodes in the tree.

Common Mistake

[X] Wrong: "Calculating height only needs to check one path from root to leaf."

[OK] Correct: The height depends on the longest path, so all nodes must be checked to be sure.

Interview Connect

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

Self-Check

"What if we stored the height at each node during insertion? How would the time complexity of getting height change?"

Practice

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

easy

A. The topmost node with no parent

B. A node with no children

C. Any node at the bottom level

D. A node with exactly two children

Solution

1. Step 1: Understand the root node concept

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

2. Step 2: Identify the correct description

   Among the options, only the topmost node with no parent matches the root node definition.

3. Final Answer:

   The topmost node with no parent -> Option A

4. Quick Check:

   Root = topmost node with no parent [OK]

Hint: Root is the very first node without a parent [OK]

Common Mistakes:

• Confusing root with leaf nodes
• Thinking root must have children
• Assuming root is any node at the bottom

2. Which of the following is the correct way to declare a simple tree node class in C# with a value and children list?

easy

A. class Node { int Value; int Children; }

B. class Node { public int Value; public Node Children; }

C. class Node { public int Value; public List<Node> Children; }

D. class Node { public int Value; public Node[] Children; }

Solution

1. Step 1: Check for correct data types and access modifiers

   The node should have a public integer value and a list of child nodes. class Node { public int Value; public List<Node> Children; } uses List<Node> which is correct.

2. Step 2: Eliminate incorrect options

   class Node { int Value; int Children; } uses int for children which is wrong. class Node { public int Value; public Node Children; } uses a single Node for children instead of a list. class Node { public int Value; public Node[] Children; } uses an array which is valid but less flexible than List.

3. Final Answer:

   class Node { public int Value; public List<Node> Children; } -> Option C

4. Quick Check:

   Use List<Node> for children in C# [OK]

Hint: Use List<Node> for multiple children in C# [OK]

Common Mistakes:

• Using int instead of List<Node> for children
• Missing public access modifier
• Using single Node instead of collection for children

3. Given a tree where the root is at level 0, what is the level of a leaf node that is 4 edges away from the root?

easy

A. 3

B. 4

C. 5

D. 6

Solution

1. Step 1: Understand level definition

   Level of a node is the number of edges from the root to that node, starting at 0 for root.

2. Step 2: Calculate leaf node level

   If leaf is 4 edges away from root, its level is 4.

3. Final Answer:

   4 -> Option B

4. Quick Check:

   Level = edges from root = 4 [OK]

Hint: Level equals number of edges from root [OK]

Common Mistakes:

• Confusing level with height
• Starting level count at 1 instead of 0
• Mixing depth and level definitions

4. Consider the following tree structure:

Node root = new Node { Value = 1, Children = new List<Node> {
  new Node { Value = 2, Children = new List<Node> {
    new Node { Value = 4, Children = new List<Node>() },
    new Node { Value = 5, Children = new List<Node>() }
  }},
  new Node { Value = 3, Children = new List<Node>() }
}};

What is the height of this tree?

medium

A. 2

B. 3

C. 1

D. 4

Solution

1. Step 1: Understand height definition

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

2. Step 2: Trace the longest path in the tree

   Longest path: root(1) -> 2 -> 4 (or 5). This path has 2 edges, so height = 2.

3. Step 3: Reconsider height counting

   Height is often defined as the number of nodes on the longest path minus 1, which equals the number of edges. The path has 3 nodes (1,2,4), so height = 2 edges, which is correct. However, some definitions count height as number of nodes, which would be 3.

4. Step 4: Confirm standard definition

   Standard definition: height = number of edges = 2.

5. Final Answer:

   2 -> Option A

6. Quick Check:

   Height = longest path edges = 2 [OK]

Hint: Height = number of edges on longest root-to-leaf path [OK]

Common Mistakes:

• Counting nodes instead of edges for height
• Confusing height with depth
• Ignoring leaf nodes at bottom

5. The following code tries to calculate the depth of a node in a tree but has a bug:

int GetDepth(Node node) {
  if (node == null) return 0;
  return 1 + GetDepth(node.Children[0]);
}

What is the main problem with this code?

medium

A. It causes infinite recursion for leaf nodes

B. It returns 0 for null nodes instead of -1

C. It does not handle the root node correctly

D. It only checks the first child, ignoring others

Solution

1. Step 1: Analyze recursion logic

   The function calls itself only on the first child (Children[0]), ignoring other children.

2. Step 2: Identify the bug impact

   This means it does not calculate depth correctly if node has multiple children; it misses deeper paths.

3. Final Answer:

   It only checks the first child, ignoring others -> Option D

4. Quick Check:

   Check all children for correct depth [OK]

Hint: Check all children, not just first, when calculating depth [OK]

Common Mistakes:

• Assuming single child trees only
• Ignoring null checks for children list
• Confusing depth with height