Two Sum in BST in DSA Rust - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main goal of the Two Sum problem in a Binary Search Tree (BST)?

To find if there exist two nodes in the BST whose values add up to a given target sum.

intermediate

Why is BST property useful in solving the Two Sum problem?

Because BST nodes are ordered, we can efficiently search for complements using in-order traversal or two-pointer techniques on sorted values.

beginner

What is one common approach to solve Two Sum in BST?

Perform an in-order traversal to get sorted node values, then use two pointers (start and end) to find if two values sum to the target.

intermediate

What is the time complexity of the two-pointer approach after in-order traversal in Two Sum BST?

O(n), where n is the number of nodes, because in-order traversal takes O(n) and two-pointer search also takes O(n).

beginner

Show a simple Rust function signature for Two Sum in BST.

fn find_target(root: Option>, k: i32) -> bool

What traversal is commonly used to get sorted values from a BST?

A Pre-order traversal

B Level-order traversal

C Post-order traversal

D In-order traversal

In-order traversal visits nodes in ascending order for BSTs.

In the Two Sum BST problem, what data structure can help check complements efficiently during traversal?

A HashSet

B Stack

C Queue

D Linked List

A HashSet can store visited values to quickly check if complement exists.

What is the main advantage of using two pointers on sorted BST values for Two Sum?

A It sorts the tree again

B It reduces time complexity to O(n)

C It requires multiple traversals

D It uses extra space for recursion

Two pointers scan the sorted list in O(n) time to find the sum.

Which Rust type is commonly used to represent a BST node with shared ownership and mutability?

A Vec<TreeNode>

B Box<TreeNode>

C Rc<RefCell<TreeNode>>

D Option<TreeNode>

Rc> allows multiple owners and interior mutability.

If the BST is empty, what should the Two Sum function return?

A false

B true

C panic

D null

No nodes means no pairs, so return false.

Explain how to solve the Two Sum problem in a BST using in-order traversal and two pointers.

Think about how sorted arrays help find pairs with a target sum.

Describe the role of Rust's Rc and RefCell in implementing a BST for the Two Sum problem.

Consider Rust's ownership rules and how to work around them for trees.

Practice

1. What is the main goal of the Two Sum in BST problem?

easy

A. Find two nodes in the BST whose values add up to a target sum.

B. Find the maximum value in the BST.

C. Count the total number of nodes in the BST.

D. Check if the BST is balanced.

Solution

1. Step 1: Understand the problem statement

   The problem asks to find two nodes in a Binary Search Tree (BST) such that their values add up to a given target sum.

2. Step 2: Clarify the goal

   We need to check if any pair of nodes exists with values summing to the target, not just find max or count nodes.

3. Final Answer:

   Find two nodes in the BST whose values add up to a target sum. -> Option A

4. Quick Check:

   Two Sum in BST = Find pair with target sum [OK]

Hint: Look for two values that add to target in BST [OK]

Common Mistakes:

• Thinking it asks for max value only
• Confusing with counting nodes
• Assuming BST must be balanced

2. Which Rust code snippet correctly defines a BST node struct for the Two Sum problem?

easy

A. struct TreeNode { val: i32, left: TreeNode, right: TreeNode }

B. struct TreeNode { val: i32, left: Option, right: Option }

C. struct TreeNode { val: i32, left: &TreeNode, right: &TreeNode }

D. struct TreeNode { val: i32, left: Option<TreeNode>, right: Option<TreeNode> }

Solution

1. Step 1: Understand Rust ownership and recursive types

   Rust requires recursive types like BST nodes to use Box or other smart pointers to allocate on heap.

2. Step 2: Check each option

   struct TreeNode { val: i32, left: Option, right: Option } uses Option which is correct. struct TreeNode { val: i32, left: TreeNode, right: TreeNode } and D use direct TreeNode which is invalid recursive type. struct TreeNode { val: i32, left: &TreeNode, right: &TreeNode } uses references without lifetimes, which is incorrect.

3. Final Answer:

   struct TreeNode { val: i32, left: Option, right: Option } -> Option B

4. Quick Check:

   Use Box for recursive BST nodes in Rust [OK]

Hint: Use Option for recursive BST nodes [OK]

Common Mistakes:

• Using direct TreeNode type causing infinite size error
• Using references without lifetimes
• Omitting Option for nullable children

3. Given the following BST and target = 9, what will the Two Sum function return?

      5
     / \
    3   6
   / \   \
  2   4   7

Rust code snippet:

fn find_target(root: &Option, k: i32) -> bool {
    let mut set = std::collections::HashSet::new();
    fn dfs(node: &Option, k: i32, set: &mut std::collections::HashSet<i32>) -> bool {
        if let Some(n) = node {
            if set.contains(&(k - n.val)) {
                return true;
            }
            set.insert(n.val);
            dfs(&n.left, k, set) || dfs(&n.right, k, set)
        } else {
            false
        }
    }
    dfs(root, k, &mut set)
}

medium

A. true

B. false

C. Compilation error

D. Runtime panic

Solution

1. Step 1: Trace DFS with HashSet on BST nodes

   Start at root 5, set is empty. Check if complement 9-5=4 in set? No. Insert 5. Check left child 3: complement 9-3=6, 6 not in set. Insert 3. Check left 2: complement 9-2=7, 7 not in set. Insert 2. Check right 4: complement 9-4=5, 5 is in set, so return true.

2. Step 2: Confirm early return on finding pair

   Since pair (5,4) sums to 9, function returns true immediately.

3. Final Answer:

   true -> Option A

4. Quick Check:

   Pair found (5+4=9) = true [OK]

Hint: Check if complement exists in set during DFS [OK]

Common Mistakes:

• Not inserting current node before checking complement
• Returning false too early
• Ignoring left or right subtree

4. Identify the bug in this Rust function for Two Sum in BST:

fn find_target(root: &Option, k: i32) -> bool {
    let mut set = std::collections::HashSet::new();
    fn dfs(node: &Option, k: i32, set: &mut std::collections::HashSet<i32>) -> bool {
        if let Some(n) = node {
            set.insert(n.val);
            if set.contains(&(k - n.val)) {
                return true;
            }
            dfs(&n.left, k, set) || dfs(&n.right, k, set)
        } else {
            false
        }
    }
    dfs(root, k, &mut set)
}

medium

A. Function does not handle empty tree.

B. Missing return statement in dfs function.

C. HashSet is not imported correctly.

D. Inserting current node value before checking complement causes false positive.

Solution

1. Step 1: Analyze order of operations in DFS

   The code inserts current node value into set before checking if complement exists. This causes the complement check to always find current value itself, leading to false positive.

2. Step 2: Correct approach

   Check if complement exists in set first, then insert current node value to avoid matching node with itself.

3. Final Answer:

   Inserting current node value before checking complement causes false positive. -> Option D

4. Quick Check:

   Check complement before insert to avoid false positive [OK]

Hint: Check complement before inserting current value [OK]

Common Mistakes:

• Inserting before checking complement
• Ignoring early return on true
• Not handling None nodes

5. You want to optimize the Two Sum in BST problem to use O(h) space, where h is tree height. Which approach is best? A BST inorder iterator yields sorted values. How can you use two iterators to solve Two Sum efficiently?

hard

A. Use a HashSet to store visited nodes and check complements during DFS.

B. Traverse BST in preorder and store all values in a vector, then use two pointers on vector.

C. Use two iterators: one from smallest to largest, another from largest to smallest, moving inward to find target sum.

D. Convert BST to linked list and then check pairs sequentially.

Solution

1. Step 1: Understand space constraints and BST properties

   Storing all nodes uses O(n) space. Using BST inorder iterator yields sorted values with O(h) space.

2. Step 2: Use two iterators moving inward

   One iterator moves from smallest to largest (inorder), another from largest to smallest (reverse inorder). Compare sums and move iterators accordingly to find target sum efficiently.

3. Step 3: Compare with other options

   Traverse BST in preorder and store all values in a vector, then use two pointers on vector. uses O(n) space. Use a HashSet to store visited nodes and check complements during DFS. uses HashSet with O(n) space. Convert BST to linked list and then check pairs sequentially. is inefficient and uses extra space.

4. Final Answer:

   Use two iterators: one from smallest to largest, another from largest to smallest, moving inward to find target sum. -> Option C

5. Quick Check:

   Two BST iterators inward = O(h) space Two Sum [OK]

Hint: Use two BST iterators from ends moving inward [OK]

Common Mistakes:

• Using full traversal storing all nodes
• Ignoring space complexity
• Not using reverse inorder iterator