Maximum Path Sum in Binary Tree in DSA Java - Time & Space Complexity

Time Complexity: Maximum Path Sum in Binary Tree

O(n)

Understanding Time Complexity

We want to know how the time needed to find the maximum path sum in a binary tree changes as the tree grows.

How does the number of steps grow when the tree has more nodes?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

private int maxSum;

public int maxPathSum(TreeNode root) {
    maxSum = Integer.MIN_VALUE;
    maxGain(root);
    return maxSum;
}

private int maxGain(TreeNode node) {
    if (node == null) return 0;
    int leftGain = Math.max(maxGain(node.left), 0);
    int rightGain = Math.max(maxGain(node.right), 0);
    int priceNewPath = node.val + leftGain + rightGain;
    maxSum = Math.max(maxSum, priceNewPath);
    return node.val + Math.max(leftGain, rightGain);
}

This code finds the maximum sum of any path in a binary tree by checking all possible paths through each node.

Identify Repeating Operations

• Primary operation: Recursive calls visiting each node once.
• How many times: Each node is visited exactly one time during recursion.

How Execution Grows With Input

Each node causes a fixed amount of work plus calls to its children. As the tree grows, the total work grows roughly with the number of nodes.

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

Pattern observation: The work grows linearly as the number of nodes increases.

Final Time Complexity

Time Complexity: O(n)

This means the time to find the maximum path sum grows directly in proportion to the number of nodes in the tree.

Common Mistake

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

[OK] Correct: Each node is visited once, and results are combined on the way back, so no repeated full visits happen.

Interview Connect

Understanding this time complexity helps you explain how efficient your solution is and shows you can analyze recursive tree problems clearly.

Self-Check

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

Practice

1. What does the Maximum Path Sum in Binary Tree problem ask you to find?

easy

A. The highest sum of values along any path in the tree

B. The longest path length in the tree

C. The smallest value in the tree

D. The number of leaf nodes in the tree

Solution

1. Step 1: Understand the problem goal

   The problem asks for the maximum sum of node values along any path in the binary tree. A path can start and end at any node but must be connected.

2. Step 2: Differentiate from other tree metrics

   It is not about path length, smallest value, or leaf count. It focuses on sum of node values along a path.

3. Final Answer:

   The highest sum of values along any path in the tree -> Option A

4. Quick Check:

   Maximum path sum = highest sum of connected nodes [OK]

Hint: Focus on sum of node values, not path length or count [OK]

Common Mistakes:

• Confusing path sum with path length
• Thinking path must start at root
• Ignoring negative values in nodes

2. Which of the following Java method signatures is correct for a function that returns the maximum path sum in a binary tree node class TreeNode?

easy

A. public void maxPathSum(TreeNode root) int

B. public int maxPathSum(TreeNode root)

C. int maxPathSum(TreeNode root) void

D. maxPathSum(TreeNode root) -> int

Solution

1. Step 1: Recall Java method syntax

   In Java, a method returning an int with public access and a parameter of type TreeNode is declared as: public int maxPathSum(TreeNode root).

2. Step 2: Check other options for syntax errors

   Options A, B, and D have invalid syntax: missing return type, misplaced void, or arrow notation not used in Java.

3. Final Answer:

   public int maxPathSum(TreeNode root) -> Option B

4. Quick Check:

   Java method syntax = public int methodName(Type param) [OK]

Hint: Remember Java method syntax: access returnType name(params) [OK]

Common Mistakes:

• Using arrow notation like other languages
• Mixing return type and void incorrectly
• Omitting access modifier

3. Given the following binary tree:

    1
   / \
  2   3

What is the maximum path sum?

medium

A. 4

B. 5

C. 3

D. 6

Solution

1. Step 1: Identify all possible paths and their sums

   Paths and sums: 2 alone = 2, 3 alone = 3, 1 alone = 1, 2->1 = 3, 3->1 = 4, 2->1->3 = 6.

2. Step 2: Find the maximum sum

   The maximum sum is 6 from path 2->1->3.

3. Final Answer:

   6 -> Option D

4. Quick Check:

   Sum(2+1+3) = 6 [OK]

Hint: Check sums including root and both children [OK]

Common Mistakes:

• Ignoring paths that go through root connecting both children
• Only considering single branches
• Adding node values incorrectly

4. Consider this Java method snippet for maximum path sum:

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

What is the main issue with this code?

medium

A. It uses Math.max instead of Math.min

B. It returns 0 for null nodes instead of Integer.MIN_VALUE

C. It does not consider paths passing through the root connecting left and right

D. It does not handle negative node values

Solution

1. Step 1: Analyze the recursive return value

   The code returns the max sum of either left or right subtree plus root value, ignoring the case where path passes through root connecting both sides.

2. Step 2: Understand maximum path sum definition

   Maximum path sum can include left subtree + root + right subtree, which this code misses.

3. Final Answer:

   It does not consider paths passing through the root connecting left and right -> Option C

4. Quick Check:

   Missing combined path sum through root [OK]

Hint: Remember max path can include both left and right subtrees [OK]

Common Mistakes:

• Ignoring combined paths through root
• Assuming max of left/right is enough
• Not updating global max path sum

5. You have a binary tree with nodes that can have negative values. Which approach correctly finds the maximum path sum?

hard

A. Use a recursive helper that returns max gain from each node, update global max with max of left + node + right, and ignore negative gains by comparing with 0

B. Sum all node values and return the total as maximum path sum

C. Only consider paths starting from root to leaf nodes

D. Use breadth-first search to find the longest path and sum its nodes

Solution

1. Step 1: Understand handling negative values

   Negative node values can reduce path sum, so ignore negative gains by comparing with 0 when calculating max gain from children.

2. Step 2: Use recursive helper with global max update

   Recursively compute max gain from left and right, update global max with left + node + right, and return max gain for parent calls.

3. Step 3: Reject incorrect approaches

   Summing all nodes ignores path constraints, root-to-leaf only misses other paths, BFS longest path ignores sums.

4. Final Answer:

   Use a recursive helper that returns max gain from each node, update global max with max of left + node + right, and ignore negative gains by comparing with 0 -> Option A

5. Quick Check:

   Recursive max gain + global max update handles negatives [OK]

Hint: Ignore negative gains by max(child, 0) in recursion [OK]

Common Mistakes:

• Summing all nodes regardless of path
• Only considering root-to-leaf paths
• Not handling negative values properly