What if you could find two numbers adding to your target without checking every pair one by one?
Why Two Sum in BST in DSA Java?
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. Without any system, you would have to check every possible pair, flipping pages back and forth endlessly.
Manually checking every pair of years is slow and tiring. It's easy to miss pairs or check the same pair twice. This wastes time and causes frustration, especially when the album is very large.
Using a Binary Search Tree (BST) and the Two Sum approach, you can quickly find if two years add up to your special number by smartly searching and comparing values without checking every pair.
for (int i = 0; i < arr.length; i++) { for (int j = i + 1; j < arr.length; j++) { if (arr[i] + arr[j] == target) return true; } }
boolean findTwoSumInBST(TreeNode root, int target) {
Set<Integer> seen = new HashSet<>();
return dfs(root, target, seen);
}
boolean dfs(TreeNode node, int target, Set<Integer> seen) {
if (node == null) return false;
if (seen.contains(target - node.val)) return true;
seen.add(node.val);
return dfs(node.left, target, seen) || dfs(node.right, target, seen);
}This lets you quickly find two numbers in a sorted tree that add up to a target, saving time and effort.
Finding two expenses in a sorted list of transactions that together match a budget limit without checking every pair.
Manual pair checking is slow and error-prone.
Two Sum in BST uses smart searching to find pairs efficiently.
This method saves time and reduces mistakes.
Practice
Two Sum in BST problem?Solution
Step 1: Understand the problem statement
The problem asks to find if there exist two nodes in the BST such that their values add up to a given target.Step 2: Identify the goal
The goal is to check for the existence of such a pair, not to find max, balance, or count nodes.Final Answer:
Find two nodes in the BST whose values add up to a target sum. -> Option CQuick Check:
Two Sum in BST means finding two nodes summing to target [OK]
- Confusing Two Sum with finding max value
- Thinking problem is about BST balance
- Counting nodes instead of finding pairs
Solution
Step 1: Understand the return type needed
The function should return true or false if a pair exists, so return type is boolean.Step 2: Check method signatures
public boolean findTarget(TreeNode root, int k) returns boolean and accepts root and target, matching the problem requirements.Final Answer:
public boolean findTarget(TreeNode root, int k) -> Option BQuick Check:
Boolean return for existence check [OK]
- Using void return type instead of boolean
- Returning int instead of boolean
- Returning TreeNode instead of boolean
findTarget(root, 9) be?
5
/ \
3 6
/ \ \
2 4 7
Solution
Step 1: Identify pairs that sum to 9
Check pairs: 2+7=9, 3+6=9, 4+5=9. All valid pairs exist.Step 2: Confirm function returns true if any pair found
Since pairs exist, function returns true.Final Answer:
true -> Option AQuick Check:
Pairs 2+7 or 3+6 sum to 9 [OK]
- Ignoring valid pairs and returning false
- Confusing output with node values
- Assuming null or error without reason
public boolean findTarget(TreeNode root, int k) {
Set<Integer> set = new HashSet<>();
return dfs(root, k, set);
}
private boolean dfs(TreeNode node, int k, Set<Integer> set) {
if (node == null) return false;
if (set.contains(k - node.val)) return true;
set.add(node.val);
dfs(node.left, k, set);
dfs(node.right, k, set);
return false;
}
What is the main bug causing incorrect results?Solution
Step 1: Analyze dfs recursive calls
dfs calls itself on left and right but ignores their return values.Step 2: Understand impact of missing returns
Without returning results of recursive calls, function always returns false unless first node matches.Step 3: Correct fix
Return true if either left or right dfs call returns true.Final Answer:
Missing return statements from recursive calls in dfs. -> Option DQuick Check:
Return recursive calls to propagate true [OK]
- Ignoring return values of recursive calls
- Using wrong data structure for lookup
- Not handling null root properly
Solution
Step 1: Understand space complexity of approaches
Storing all nodes uses O(n) space; HashSet also O(n); array conversion O(n).Step 2: Two iterator approach
Using two iterators (in-order and reverse in-order) simulates two pointers with O(h) space.Step 3: Choose best approach
Use two iterators: one in-order and one reverse in-order traversal. uses O(h) space and is optimal for BST Two Sum.Final Answer:
Use two iterators: one in-order and one reverse in-order traversal. -> Option AQuick Check:
Two iterators give O(h) space [OK]
- Using full list storage causing O(n) space
- Relying on HashSet which uses O(n) space
- Ignoring BST properties for optimization
Ready to prove it?
Pass the test and this pattern moves unknown
