Diameter of Binary Tree in DSA Java - Time & Space Complexity

Time Complexity: Diameter of Binary Tree

O(n)

Understanding Time Complexity

We want to know how long it takes to find the diameter of a binary tree as the tree grows.

The question is: how does the work increase when the tree has more nodes?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

public class TreeNode {
    int val;
    TreeNode left, right;
    TreeNode(int x) { val = x; }
}

public class Solution {
    int diameter = 0;
    public int diameterOfBinaryTree(TreeNode root) {
        depth(root);
        return diameter;
    }
    private int depth(TreeNode node) {
        if (node == null) return 0;
        int left = depth(node.left);
        int right = depth(node.right);
        diameter = Math.max(diameter, left + right);
        return Math.max(left, right) + 1;
    }
}

This code finds the longest path between any two nodes in a binary tree by checking depths of subtrees.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Recursive calls to visit each node once.
• How many times: Each node is visited exactly one time.

How Execution Grows With Input

As the number of nodes grows, the function visits each node once to calculate depths.

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

Pattern observation: The work grows directly with the number of nodes, so doubling nodes doubles work.

Final Time Complexity

Time Complexity: O(n)

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

Common Mistake

[X] Wrong: "The code visits nodes multiple times, so time is more than linear."

[OK] Correct: Each node is visited once in the recursion, and depth is calculated on the way back, so no repeated full visits.

Interview Connect

Understanding this linear time approach shows you can handle tree problems efficiently, a key skill in many coding challenges.

Self-Check

"What if we changed the code to calculate diameter by checking all pairs of nodes? How would the time complexity change?"

Practice

1. What does the diameter of a binary tree represent?

easy

A. The number of leaf nodes in the tree

B. The length of the longest path between any two nodes in the tree

C. The height of the tree

D. The total number of nodes in the tree

Solution

1. Step 1: Understand the diameter definition

   The diameter is the longest path between any two nodes, which may or may not pass through the root.

2. Step 2: Differentiate from other tree properties

   Height is the longest path from root to leaf, leaf count is number of leaves, total nodes is size, none of which define diameter.

3. Final Answer:

   The length of the longest path between any two nodes in the tree -> Option B

4. Quick Check:

   Diameter = Longest path between nodes [OK]

Hint: Diameter is longest path between any two nodes [OK]

Common Mistakes:

• Confusing diameter with height
• Thinking diameter counts nodes instead of edges
• Assuming diameter must pass through root

2. Which of the following Java method signatures correctly represents a recursive function to find the diameter of a binary tree node?

easy

A. public int diameter(int root)

B. public void diameter(TreeNode root)

C. public String diameter(TreeNode root)

D. public int diameter(TreeNode root)

Solution

1. Step 1: Identify correct parameter type

   The method must accept a TreeNode object representing the root of the tree or subtree.

2. Step 2: Identify correct return type

   Diameter is a number (int), so return type should be int, not void or String.

3. Final Answer:

   public int diameter(TreeNode root) -> Option D

4. Quick Check:

   Method returns int and takes TreeNode [OK]

Hint: Diameter method returns int and takes TreeNode [OK]

Common Mistakes:

• Using void return type for diameter
• Passing int instead of TreeNode
• Returning String instead of int

3. Given the following binary tree code snippet, what is the diameter of the tree?

class TreeNode {
  int val;
  TreeNode left, right;
  TreeNode(int x) { val = x; }
}

TreeNode root = new TreeNode(1);
root.left = new TreeNode(2);
root.right = new TreeNode(3);
root.left.left = new TreeNode(4);
root.left.right = new TreeNode(5);

// Diameter calculation code omitted for brevity

medium

A. 2

B. 5

C. 3

D. 4

Solution

1. Step 1: Visualize the tree structure

   The tree has root 1, left child 2 with children 4 and 5, and right child 3.

2. Step 2: Find longest path between any two nodes

   Longest path is from node 4 to node 3 via 2 and 1: path 4->2->1->3 = 3 edges, diameter = 3.

3. Final Answer:

   3 -> Option C

4. Quick Check:

   Longest path length = 3 edges [OK]

Hint: Count edges on longest path between two nodes [OK]

Common Mistakes:

• Counting nodes instead of edges or vice versa
• Ignoring paths not passing through root
• Miscounting edges in path

4. Identify the bug in this diameter calculation method and select the fix:

int diameter = 0;
int height(TreeNode root) {
  if (root == null) return 0;
  int left = height(root.left);
  int right = height(root.right);
  diameter = Math.max(diameter, left + right);
  return Math.max(left, right);
}

medium

A. Return Math.max(left, right) + 1 instead of Math.max(left, right)

B. Initialize diameter inside height method

C. Use diameter = Math.min(diameter, left + right)

D. Return left + right instead of Math.max(left, right)

Solution

1. Step 1: Understand height calculation

   Height of a node is 1 plus max height of its children, so must add +1.

2. Step 2: Identify bug in return statement

   Current code returns max(left, right) without +1, so height is underestimated.

3. Final Answer:

   Return Math.max(left, right) + 1 instead of Math.max(left, right) -> Option A

4. Quick Check:

   Height = max child height + 1 [OK]

Hint: Height adds 1 to max child height [OK]

Common Mistakes:

• Forgetting to add +1 in height return
• Using min instead of max for diameter update
• Returning sum of left and right as height

5. You want to find the diameter of a binary tree but also print the nodes on the longest path. Which approach is best?

hard

A. Modify the diameter function to store and return the longest path nodes along with diameter

B. Calculate diameter first, then do a separate BFS to find longest path nodes

C. Use only height function and print nodes at max height

D. Count leaf nodes and assume longest path is between two leaves

Solution

1. Step 1: Understand diameter and path relationship

   Diameter is longest path length; to print nodes, we must track path during diameter calculation.

2. Step 2: Choose approach that combines diameter and path tracking

   Modifying diameter function to store nodes on longest path is efficient and direct.

3. Final Answer:

   Modify the diameter function to store and return the longest path nodes along with diameter -> Option A

4. Quick Check:

   Track path during diameter calc for nodes [OK]

Hint: Track nodes while computing diameter for path [OK]

Common Mistakes:

• Running BFS separately wastes time
• Assuming height equals diameter path
• Counting leaves without path tracking