Kth Employee Reached in an Ordered Hierarchy
UberSoftware Engineer · Online AssessmentLast updated
This problem tests tree traversal techniques, specifically finding the k-th node in an in-order traversal of a binary search tree while handling dynamic updates or specific subtree constraints.
Problem Statement
You are given a binary tree representing the organizational hierarchy of a company. Each node in the tree has a unique integer ID. An employee's 'rank' is determined by their position in an in-order traversal of the tree.
Your task is to implement a function that returns the ID of the k-th employee (1-indexed) in the in-order traversal of the hierarchy rooted at a given node. If the subtree contains fewer than k nodes, return -1.
Function Signature
class TreeNode:
def __init__(self, val=0, left=None, right=None):
self.val = val
self.left = left
self.right = right
def get_kth_employee(root: TreeNode, k: int) -> int:
Constraints
- The number of nodes
nin the tree is up to 10^5. 1 <= k <= n.- The tree structure is fixed for each query.
Examples
Example 1:
- Input: root = [3, 1, 4, null, 2], k = 2
- Tree structure: Node 3 has left child 1 and right child 4. Node 1 has right child 2.
- In-order traversal: [1, 2, 3, 4]
- Output: 2
Example 2:
- Input: root = [5, 3, 6], k = 4
- In-order traversal: [3, 5, 6]
- Output: -1
Edge Cases
- Tree with only one node.
- k being larger than the total number of nodes.
- A highly skewed tree (resembling a linked list).
Hints
Hint 1
An in-order traversal of a binary tree visits nodes in the sequence: left subtree, root, right subtree.
Hint 2
If you know the size of the left subtree, you can determine if the k-th node is in the left subtree, is the root itself, or lies in the right subtree.
Hint 3
Consider augmenting the tree nodes to store the size of the subtree rooted at each node during a preprocessing step to allow for O(height) query time.
Follow-up questions
- How would your approach change if nodes could be added or removed from the tree dynamically?
- If you needed to perform millions of queries on the same static tree, how could you optimize the query time complexity beyond O(n)?
- How would you handle the memory constraints if the tree is extremely deep (e.g., depth of 10^5) to avoid recursion depth issues?
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