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DSA C++programming~3 mins

Why Two Sum in BST in DSA C++?

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The Big Idea

What if you could find two numbers adding to your target in a tree without checking every pair?

The Scenario

Imagine you have a big family photo album sorted by year, and you want to find two photos whose years add up to a special number. You try flipping through pages manually, checking every pair, but it takes forever.

The Problem

Manually checking every pair of photos means looking at many combinations, which is slow and tiring. You might miss pairs or repeat checks, making it error-prone and frustrating.

The Solution

Using the Two Sum approach in a Binary Search Tree (BST) lets you quickly find two numbers that add up to the target by smartly navigating the tree. It avoids checking all pairs and finds the answer faster and more reliably.

Before vs After
✗ Before
for (auto it1 = nums.begin(); it1 != nums.end(); ++it1) {
  for (auto it2 = it1 + 1; it2 != nums.end(); ++it2) {
    if (*it1 + *it2 == target) return true;
  }
}
✓ After
bool findTwoSumInBST(TreeNode* root, int target) {
  // Use two pointers with BST iterators to find sum
}
What It Enables

This concept enables fast and efficient searching for pairs in sorted tree data without checking every combination.

Real Life Example

Finding two expenses in a sorted list of transactions that add up to a specific budget limit quickly without scanning all pairs.

Key Takeaways

Manual pair checking is slow and error-prone.

Two Sum in BST uses tree properties for faster search.

It saves time and reduces mistakes in finding pairs.

Practice

(1/5)
1. What is the main goal of the Two Sum in BST problem?
easy
A. Find the maximum value in a BST
B. Find two nodes in a BST whose values add up to a target sum
C. Count the number of nodes in a BST
D. Check if a BST is balanced

Solution

  1. Step 1: Understand the problem statement

    The problem asks to find if there exist two nodes in a Binary Search Tree (BST) such that their values add up to a given target sum.
  2. Step 2: Identify the goal

    The goal is to check for the existence of such a pair, not to find maximum, count nodes, or check balance.
  3. Final Answer:

    Find two nodes in a BST whose values add up to a target sum -> Option B
  4. Quick Check:

    Two Sum in BST means finding two nodes summing to target [OK]
Hint: Look for two nodes adding to target in BST [OK]
Common Mistakes:
  • Confusing with finding max/min value
  • Thinking it counts nodes instead of pairs
  • Assuming it checks tree balance
2. Which of the following C++ code snippets correctly declares a BST node structure for the Two Sum problem?
easy
A. struct TreeNode { int val; TreeNode left; TreeNode* right; };
B. struct TreeNode { int val; TreeNode left; TreeNode right; };
C. struct TreeNode { int val; TreeNode* left; TreeNode* right; };
D. struct TreeNode { int val; TreeNode* left; TreeNode right; };

Solution

  1. Step 1: Check pointer usage in struct

    In C++, child nodes in a tree are pointers to TreeNode objects, so left and right must be pointers.
  2. Step 2: Validate each option

    struct TreeNode { int val; TreeNode* left; TreeNode* right; }; uses TreeNode* for left and right, which is correct. Options A, B, and C incorrectly use TreeNode without pointers for one or both children.
  3. Final Answer:

    struct TreeNode { int val; TreeNode* left; TreeNode* right; }; -> Option C
  4. Quick Check:

    BST nodes use pointers for children [OK]
Hint: Children in BST nodes are pointers in C++ [OK]
Common Mistakes:
  • Using objects instead of pointers for children
  • Mixing pointer and non-pointer types
  • Forgetting semicolon after struct
3. What is the output of the following code snippet that checks for two sum in BST?
struct TreeNode {
  int val;
  TreeNode* left;
  TreeNode* right;
  TreeNode(int x) : val(x), left(nullptr), right(nullptr) {}
};

bool findTarget(TreeNode* root, int k) {
  std::unordered_set<int> seen;
  std::function dfs = [&](TreeNode* node) {
    if (!node) return false;
    if (seen.count(k - node->val)) return true;
    seen.insert(node->val);
    return dfs(node->left) || dfs(node->right);
  };
  return dfs(root);
}

int main() {
  TreeNode* root = new TreeNode(5);
  root->left = new TreeNode(3);
  root->right = new TreeNode(6);
  root->left->left = new TreeNode(2);
  root->left->right = new TreeNode(4);
  root->right->right = new TreeNode(7);
  
  bool result = findTarget(root, 9);
  std::cout << (result ? "true" : "false") << std::endl;
  return 0;
}
medium
A. true
B. false
C. Compilation error
D. Runtime error

Solution

  1. Step 1: Understand the tree and target

    The BST has nodes 5,3,6,2,4,7. The target sum is 9.
  2. Step 2: Trace the DFS and set usage

    DFS visits nodes and checks if (target - current node value) is in the set. For example, when visiting node 6, it checks if 9-6=3 is in set. Node 3 was visited before, so it returns true.
  3. Final Answer:

    true -> Option A
  4. Quick Check:

    3 + 6 = 9 found in BST [OK]
Hint: Check if complement exists in visited nodes set [OK]
Common Mistakes:
  • Assuming no pair exists without checking all nodes
  • Confusing DFS order with BFS
  • Ignoring the use of hash set for complements
4. Identify the bug in the following Two Sum in BST code snippet and select the correct fix:
bool findTarget(TreeNode* root, int k) {
  std::unordered_set<int> seen;
  std::function dfs = [&](TreeNode* node) {
    if (!node) return false;
    if (seen.count(k - node->val)) return true;
    dfs(node->left);
    dfs(node->right);
    seen.insert(node->val);
    return false;
  };
  return dfs(root);
}
medium
A. Insert node->val before recursive calls to children
B. Remove the unordered_set and use a vector instead
C. Change return false to return true at the end
D. Add a null check after inserting node->val

Solution

  1. Step 1: Analyze the order of operations

    The code inserts node->val into the set after recursive calls, so complements are not found when visiting children.
  2. Step 2: Fix the insertion timing

    Insert node->val before recursive calls so that children can find complements in the set.
  3. Final Answer:

    Insert node->val before recursive calls to children -> Option A
  4. Quick Check:

    Insert before recursion to find complements [OK]
Hint: Insert current value before recursion to detect complements [OK]
Common Mistakes:
  • Inserting after recursion causes missed pairs
  • Changing return values incorrectly
  • Replacing set with vector reduces efficiency
5. Given a BST with nodes [10, 5, 15, 3, 7, null, 18], how would you modify the Two Sum in BST algorithm to handle the case where the target sum is twice the value of a single node (e.g., target = 14 and node value = 7)?
hard
A. Only check leaf nodes for pairs
B. Ignore pairs where complement equals current node value
C. Use a sorted array instead of a hash set
D. Check if the complement equals the current node value and ensure the node appears twice

Solution

  1. Step 1: Understand the problem with duplicates

    If target is twice a node's value, we must ensure two distinct nodes with that value exist.
  2. Step 2: Modify algorithm to handle duplicates

    When complement equals current node value, check if the node appears twice (e.g., by counting occurrences or checking different nodes).
  3. Final Answer:

    Check if the complement equals the current node value and ensure the node appears twice -> Option D
  4. Quick Check:

    Handle duplicates by verifying two distinct nodes [OK]
Hint: Verify two distinct nodes if complement equals current value [OK]
Common Mistakes:
  • Ignoring duplicate values causing false positives
  • Skipping pairs with same node value
  • Switching data structures unnecessarily
Recommended

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