Bytedance·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say

Apr 2026

Summary

Bytedance infra interview, one meaty tree problem that took up most of the session. The design discussion afterward felt like the real test honestly.

Questions Asked (1)

Given a binary tree (not necessarily a BST) and a target node, delete that node and reconnect its children so the result is still a valid binary tree. Walk through your reconnection policy and the time complexity.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I went with promoting the deepest rightmost leaf as the replacement, which felt clean to me, but the interviewer kept pushing on whether that was the only valid approach or just one option.

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AI HintsAI Generated

Suggested Approach

Clarify the reconnection policy upfront, then present a clean recursive solution that replaces the deleted node with its left child and attaches the right subtree to the rightmost node of that left subtree. Analyze time complexity as O(h) for deletion plus O(h) for finding the rightmost node, giving O(h) overall, and discuss trade-offs with alternative policies.

Pro tip: Mention that the choice of reconnection policy depends on whether the tree is balanced or if you want to preserve in-order traversal; for a general binary tree, attaching the right subtree to the rightmost node of the left subtree is a common and efficient approach.

1. Clarify the problem and constraints

Ask whether the tree is balanced, whether there are parent pointers, and if any reconnection policy is preferred. Confirm that the tree is not a BST and that we need to maintain a valid binary tree structure.

2. Choose a reconnection policy

Decide on a policy: e.g., replace the node with its left child and attach the right subtree to the rightmost node of the left subtree. Alternatively, replace with the right child and attach the left subtree to the leftmost node of the right subtree.

3. Implement the deletion recursively

Write a function that traverses the tree to find the target node. Once found, apply the chosen reconnection policy and return the new subtree root to the parent.

4. Analyze time and space complexity

Explain that finding the node takes O(h) time, and finding the rightmost node also takes O(h) in the worst case, so overall O(h) time. Space complexity is O(h) due to recursion stack.

5. Discuss edge cases and trade-offs

Cover cases: node is root, node has no left child, node has no right child, node is leaf. Discuss trade-offs: balancing vs. simplicity, and how different policies affect tree height.

Key Points to Mention

Reconnection policy: replace with left child and attach right subtree to rightmost node of left subtree.
Time complexity: O(h) for finding the node plus O(h) for finding the rightmost node, so O(h) overall.
Space complexity: O(h) due to recursion stack.
Edge cases: deleting root, leaf, node with only one child.
Alternative policies: replace with right child and attach left subtree to leftmost node of right subtree.
Trade-offs: policy affects tree balance and future operations.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.