DP on Trees Maximum Path Sum in DSA C++ - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main idea behind using dynamic programming on trees to find the maximum path sum?

We break the problem into smaller parts by computing the maximum path sum starting from each node and use these results to find the overall maximum path sum in the tree.

beginner

In the context of maximum path sum on trees, what does the 'path' mean?

A path is any sequence of nodes connected by edges, where each node appears only once. It can start and end at any nodes in the tree.

intermediate

Why do we consider only one child path when returning the maximum sum to the parent node in DP on trees maximum path sum?

Because the path going up to the parent can only continue through one child, so we choose the child path with the maximum sum to extend upwards.

intermediate

What is the role of a global variable in the DP on trees maximum path sum algorithm?

It keeps track of the overall maximum path sum found so far while exploring all nodes, since the maximum path may not pass through the root.

intermediate

Explain why negative path sums are ignored or replaced with zero in the DP on trees maximum path sum solution.

Negative sums reduce the total path sum, so we ignore them by replacing with zero to avoid decreasing the maximum path sum.

In DP on trees maximum path sum, what does the recursive function typically return?

A Maximum path sum starting from the current node and going down to one child

B Maximum path sum including both children and the current node

C Sum of all nodes in the tree

D Number of nodes in the longest path

The function returns the maximum sum path starting at the current node and extending down to one child, to be used by the parent.

Why do we update the global maximum path sum with the sum of left child, right child, and current node?

A Because the path must include both children always

B Because the maximum path can pass through the current node connecting both children

C Because the path sum is always the sum of all nodes

D Because the current node is always the root

The maximum path may pass through the current node connecting left and right child paths, so we consider their sum plus current node.

What should be done if the maximum path sum from a child is negative?

A Ignore it by treating it as zero

B Stop the recursion

C Multiply it by -1

D Include it as is

Negative sums reduce the total, so we ignore them by treating as zero to maximize the path sum.

Which data structure is essential to represent the tree in DP on trees maximum path sum?

A Array

B Linked list

C Tree nodes with left and right pointers

D Stack

The tree is represented by nodes having pointers to left and right children.

What is the time complexity of DP on trees maximum path sum algorithm?

A O(n^2)

B O(n log n)

C O(log n)

D O(n)

Each node is visited once, so the time complexity is linear in the number of nodes.

Describe the steps to find the maximum path sum in a binary tree using dynamic programming.

Think about how to combine child results and update global max.

Explain why the maximum path sum in a tree may not include the root node.

Consider that the path is not restricted to root-to-leaf.

Practice

1. What does the "Maximum Path Sum" in a tree represent in the context of dynamic programming on trees?

easy

A. The largest sum of node values on any path between two nodes in the tree

B. The sum of all node values in the tree

C. The maximum value of a single node in the tree

D. The longest path length in the tree

Solution

1. Step 1: Understand the problem definition

   The maximum path sum is the highest sum of values collected by traveling along any path between two nodes in the tree, not necessarily passing through the root.

2. Step 2: Differentiate from other sums

   It is not the sum of all nodes or just the maximum node value, but the maximum sum along any connected path.

3. Final Answer:

   The largest sum of node values on any path between two nodes in the tree -> Option A

4. Quick Check:

   Maximum path sum = largest sum on any node-to-node path [OK]

Hint: Maximum path sum is about any path, not whole tree sum [OK]

Common Mistakes:

• Confusing maximum path sum with total sum of all nodes
• Thinking it is the maximum single node value
• Assuming path must start at root

2. Which of the following C++ function signatures is correct for a recursive function that computes the maximum path sum in a binary tree node structure defined as struct TreeNode { int val; TreeNode* left; TreeNode* right; };?

easy

A. int maxPathSum(TreeNode root);

B. void maxPathSum(TreeNode root);

C. int maxPathSum(TreeNode* root);

D. int maxPathSum(TreeNode* root, int sum);

Solution

1. Step 1: Check parameter passing

   The tree nodes should be passed as pointers to avoid copying the entire subtree, so TreeNode* is correct.

2. Step 2: Check return type and parameters

   The function returns an integer representing the maximum path sum, so int return type is correct. Additional parameters like int sum are not necessary for the main function signature.

3. Final Answer:

   int maxPathSum(TreeNode* root); -> Option C

4. Quick Check:

   Use pointer parameter and int return type [OK]

Hint: Use pointer parameter and int return type for tree recursion [OK]

Common Mistakes:

• Passing TreeNode by value causing copies
• Using void return type when int is needed
• Adding unnecessary parameters in main signature

3. Consider the following C++ code snippet for maximum path sum in a binary tree:

struct TreeNode { int val; TreeNode* left; TreeNode* right; };

int maxSum = INT_MIN;

int dfs(TreeNode* node) {
  if (!node) return 0;
  int left = max(0, dfs(node->left));
  int right = max(0, dfs(node->right));
  maxSum = max(maxSum, node->val + left + right);
  return node->val + max(left, right);
}

int maxPathSum(TreeNode* root) {
  dfs(root);
  return maxSum;
}

// Tree structure:
//       1
//      / \
//     2   3
//
// What is the output of maxPathSum(root)?

medium

A. 5

B. 6

C. 3

D. 1

Solution

1. Step 1: Calculate dfs values for each node

   For leaf nodes 2 and 3, dfs returns their values (2 and 3). For root 1, left=2, right=3, so maxSum = max(INT_MIN, 1+2+3) = 6.

2. Step 2: Return maxSum after dfs completes

   The function returns maxSum = 6, which is the maximum path sum (2 -> 1 -> 3).

3. Final Answer:

   6 -> Option B

4. Quick Check:

   Max path sum = 2 + 1 + 3 = 6 [OK]

Hint: Add node value plus max left and right sums, ignore negatives [OK]

Common Mistakes:

• Ignoring max(0, dfs(...)) causing negative sums
• Returning node->val + left + right instead of max path
• Confusing maxSum update with return value

4. The following code attempts to compute the maximum path sum in a binary tree but has a bug:

int maxSum = INT_MIN;

int dfs(TreeNode* node) {
  if (!node) return 0;
  int left = dfs(node->left);
  int right = dfs(node->right);
  maxSum = max(maxSum, node->val + left + right);
  return node->val + max(left, right);
}

What is the main issue causing incorrect results?

medium

A. It does not handle null nodes properly

B. It returns the sum of both children instead of max

C. It does not update maxSum correctly

D. It does not ignore negative sums from children

Solution

1. Step 1: Analyze child sums usage

   The code uses raw dfs values for left and right without ignoring negative sums, which can reduce the path sum.

2. Step 2: Identify fix for negative sums

   To fix, use max(0, dfs(...)) to ignore negative sums from children, ensuring path sum only increases or stays same.

3. Final Answer:

   It does not ignore negative sums from children -> Option D

4. Quick Check:

   Use max(0, dfs(child)) to avoid negative sums [OK]

Hint: Always ignore negative child sums with max(0, dfs(child)) [OK]

Common Mistakes:

• Not using max(0, ...) causing negative path sums
• Returning sum of both children instead of max for recursion
• Incorrect maxSum update logic

5. Given a binary tree where nodes can have negative values, how would you modify the standard maximum path sum algorithm to correctly handle the case where the maximum path sum is a single node with a negative value? Choose the best approach.

hard

A. Initialize maxSum with INT_MIN and use max(0, dfs(child)) in recursion

B. Initialize maxSum with 0 and ignore negative node values completely

C. Initialize maxSum with INT_MIN and allow dfs to return negative values without max(0, ...)

D. Initialize maxSum with 0 and always add node values regardless of sign

Solution

1. Step 1: Recall the standard algorithm

   The standard algorithm initializes maxSum to INT_MIN and uses left = max(0, dfs(left)), right = max(0, dfs(right)), updating maxSum = max(maxSum, node.val + left + right). This captures single negative nodes as node.val + 0 + 0.

2. Step 2: Why it handles negatives

   max(0, dfs(child)) prevents extending to negative subtrees but allows dfs to return node.val + 0 (negative if node negative). INT_MIN init captures negative maxima.

3. Step 3: Why A fails

   Without max(0, ...), negative child sums pollute parent updates (e.g., root=-2, left=-3: maxSum wrongly stays -3 instead of -2).

4. Final Answer:

   Initialize maxSum with INT_MIN and use max(0, dfs(child)) in recursion -> Option A

5. Quick Check:

   max(0, dfs(child)) + INT_MIN handles negative single nodes [OK]

Hint: Standard max(0, dfs(child)) + INT_MIN handles negative nodes correctly [OK]

Common Mistakes:

• Omitting max(0, ...) letting negative children reduce parent path sums
• Initializing maxSum with 0 missing negative maxima
• Ignoring all negative nodes