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

Recall & Review

beginner

What is the main goal of the "DP on Trees Maximum Path Sum" problem?

To find the maximum sum of values along any path in a tree, where a path can start and end at any nodes.

beginner

In the context of DP on trees, what does the term "path" mean?

A sequence of connected nodes in the tree, where each pair of consecutive nodes is connected by an edge, and no node is repeated.

intermediate

Why do we use recursion with memoization or DP in the maximum path sum on trees?

Because we want to efficiently compute the maximum path sums for subtrees and reuse these results to avoid repeated calculations.

intermediate

What is the significance of considering both "single path" and "split path" sums in this problem?

Single path sums represent the max sum from a node down to one child, while split path sums consider paths passing through the node connecting two children, helping find the global max path.

intermediate

How do negative node values affect the maximum path sum calculation in trees?

Negative values can reduce path sums, so we often ignore paths with negative sums by comparing with zero to avoid decreasing the total sum.

In DP on Trees Maximum Path Sum, what does the recursive function usually return?

A Height of the tree

B Total number of nodes in the tree

C Minimum path sum in the tree

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

The recursive function returns the maximum sum of a path starting at the current node and going down to one child to help build larger path sums.

Which of these is NOT considered when calculating the maximum path sum in a tree?

A Path passing through the current node connecting two children

B Path starting and ending at the same node

C Path that includes cycles

D Path going down from the current node to one child

Trees do not have cycles, so paths including cycles are not considered.

Why do we compare child path sums with zero in DP on Trees Maximum Path Sum?

A To ignore negative sums that reduce the total path sum

B To count the number of children

C To find the minimum path sum

D To calculate the height of the tree

Comparing with zero helps ignore negative sums, ensuring we only add positive contributions to the path sum.

What data structure is commonly used to represent the tree in this problem?

A Queue

B Adjacency list

C Stack

D Hash map

An adjacency list is commonly used to represent trees for efficient traversal.

What is the time complexity of the DP on Trees Maximum Path Sum algorithm?

A O(n), where n is the number of nodes

B O(n^2)

C O(log n)

D O(1)

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

Explain how to use recursion and dynamic programming to find the maximum path sum in a tree.

Think about how to combine child results and update the answer.

Describe the difference between a single path and a split path in the context of maximum path sum on trees.

Focus on how paths are formed and used in calculations.

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 along any path between two nodes in the tree

B. The number of nodes in the longest path of the tree

C. The sum of all node values in the tree

D. The height of the tree

Solution

1. Step 1: Understand the problem definition

   The maximum path sum is about finding the path between any two nodes that yields the highest sum of node values.

2. Step 2: Differentiate from other tree properties

   Unlike longest path or height, maximum path sum focuses on the sum of node values, not count or depth.

3. Final Answer:

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

4. Quick Check:

   Maximum path sum = largest node value sum [OK]

Hint: Maximum path sum is about sums, not counts or heights [OK]

Common Mistakes:

• Confusing maximum path sum with longest path length
• Thinking it is the sum of all nodes
• Mixing it up with tree height

2. Which of the following is the correct base case initialization for a recursive function computing maximum path sum in a binary tree node in C?

easy

A. if (node == NULL) return INT_MIN;

B. if (node == NULL) return -1;

C. if (node == NULL) return 1;

D. if (node == NULL) return 0;

Solution

1. Step 1: Understand base case for null nodes

   For maximum path sum, null nodes should contribute 0 to the path sum as they do not add any value.

2. Step 2: Choose appropriate return value

   Returning 0 ensures that null nodes do not affect the sum and allows the recursion to proceed correctly.

3. Final Answer:

   if (node == NULL) return 0; -> Option D

4. Quick Check:

   Base case returns 0 to represent no contribution from null nodes [OK]

Hint: Use 0 for null nodes to avoid affecting sums [OK]

Common Mistakes:

• Returning INT_MIN which can cause incorrect sums
• Returning positive values for null nodes
• Returning 1 or -1 which are arbitrary and incorrect

3. Consider the following C code snippet for maximum path sum in a binary tree node structure. What is the output printed by printf("%d", maxSum); after calling maxPathSum(root); on the tree below?

Tree structure:
1
/ \\
2 3

typedef struct Node {
    int val;
    struct Node* left;
    struct Node* right;
} Node;

int maxSum = INT_MIN;

int maxPathSumUtil(Node* root) {
    if (!root) return 0;
    int left = maxPathSumUtil(root->left);
    int right = maxPathSumUtil(root->right);
    int maxSingle = (left > right ? left : right) + root->val;
    int maxTop = (left + right + root->val);
    if (maxTop > maxSum) maxSum = maxTop;
    return maxSingle > root->val ? maxSingle : root->val;
}

int maxPathSum(Node* root) {
    maxSum = INT_MIN;
    maxPathSumUtil(root);
    return maxSum;
}

medium

A. 3

B. 5

C. 6

D. 4

Solution

1. Step 1: Calculate max path sums for each node

   For node 2 and 3, maxSingle = 2 and 3 respectively, maxTop = 2 and 3. For root 1, left=2, right=3, maxSingle = max(2,3)+1=4, maxTop=2+3+1=6.

2. Step 2: Update maxSum and return final value

   maxSum updates to 6 at root. The function returns maxSum = 6.

3. Final Answer:

   6 -> Option C

4. Quick Check:

   Sum of path 2->1->3 = 6 [OK]

Hint: Sum path through root and children for max sum [OK]

Common Mistakes:

• Ignoring path through both children
• Returning maxSingle instead of maxSum
• Not updating global maxSum correctly

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

int maxSum = INT_MIN;

int maxPathSumUtil(Node* root) {
    if (!root) return 0;
    int left = maxPathSumUtil(root->left);
    int right = maxPathSumUtil(root->right);
    int maxSingle = (left > right ? left : right) + root->val;
    int maxTop = (left + right + root->val);
    if (maxSingle > maxSum) maxSum = maxSingle;
    if (maxTop > maxSum) maxSum = maxTop;
    return maxSingle;
}

medium

A. It returns maxSingle without comparing it to root->val

B. It updates maxSum with maxSingle before maxTop, missing some max sums

C. It does not handle negative node values correctly

D. It returns maxSingle but should return maxTop

Solution

1. Step 1: Check return value correctness

   maxSingle should be max of (maxSingle, root->val) to handle negative values properly.

2. Step 2: Identify missing max comparison

   Without comparing maxSingle to root->val, the function may return a smaller sum than root's value alone.

3. Final Answer:

   It returns maxSingle without comparing it to root->val -> Option A

4. Quick Check:

   Return value must consider root->val for negatives [OK]

Hint: Always compare maxSingle with root->val before returning [OK]

Common Mistakes:

• Not handling negative values correctly
• Updating maxSum incorrectly
• Returning maxTop instead of maxSingle

5. Given a binary tree where nodes can have negative values, which approach correctly computes the maximum path sum using dynamic programming on trees?

hard

A. Use a recursive function that returns the maximum path sum including the current node and one child, update a global max with sum of node and both children, and handle negative values by comparing with zero

B. Use a recursive function that returns the maximum path sum including the current node and one child, update a global max with sum of node and both children, and handle negative values by comparing with the node's value itself

C. Use a recursive function that returns the sum of all nodes in the subtree, ignoring negative values, and update global max accordingly

D. Use a recursive function that returns the maximum path sum including the current node and both children always, without any comparison for negative values

Solution

1. Step 1: Understand handling of negative values

   Negative values require comparing max sums with the node's own value to avoid reducing sums by adding negative children.

2. Step 2: Correct recursive approach

   Return max path sum including current node and one child or node alone; update global max with sum of node and both children.

3. Final Answer:

   Use a recursive function that returns the maximum path sum including the current node and one child, update a global max with sum of node and both children, and handle negative values by comparing with the node's value itself -> Option B

4. Quick Check:

   Compare with node value to handle negatives correctly [OK]

Hint: Compare sums with node value itself to handle negatives [OK]

Common Mistakes:

• Ignoring negative values in sums
• Always adding both children without max checks
• Ignoring node's own value in comparisons