Knew immediately it was an in-order traversal thing since BST in-order gives you sorted order.
Use an in-order traversal of the BST to visit nodes in ascending order, counting until you reach the kth node. Alternatively, if the tree is large and k is small, use an iterative stack-based traversal to avoid recursion overhead and allow early termination.
Pro tip: Mention that you can optimize by storing the size of each subtree in the nodes (if modifications are allowed) to achieve O(log n) time, but clarify that this requires extra space and preprocessing. This shows awareness of trade-offs.
Ask about tree size, whether k is guaranteed valid, and if the tree can be modified. This helps choose the right approach.
Decide between recursive in-order traversal (simple but O(n) space for recursion) and iterative stack-based traversal (O(h) space, early termination).
Write code to traverse the BST in ascending order, keeping a counter. Stop when the counter equals k and return the current node's value.
State time complexity O(n) worst-case, but O(k) if early termination; space complexity O(h) for iterative, O(n) for recursive.
Mention augmenting the tree with subtree sizes to achieve O(log n) time if frequent queries are expected.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.