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Microsoft·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jun 2026

Summary

Microsoft coding round, one tree problem, pretty standard stuff but worth knowing the two approaches cold before you walk in.

Questions Asked (1)

Q1

Given the root of a binary tree, return its level-order traversal ordered from the deepest level up to the root.

Algorithms & Data Structures
Author's notes

I went straight for BFS, collected each level into its own list, then reversed at the end.

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AI HintsAI Generated

Suggested Approach

Use a breadth-first search (BFS) to perform a standard level-order traversal from the root, collecting nodes level by level. Then reverse the order of the levels to get the traversal from deepest to root. Alternatively, use depth-first search (DFS) to record nodes at each depth and then reverse the levels.

Pro tip: Clarify with the interviewer whether 'deepest level up to the root' means reversing the order of levels while keeping nodes within each level left-to-right, or also reversing nodes within each level. This shows attention to detail and avoids misinterpretation.

1. Clarify the problem

Confirm the expected output format: list of lists where each inner list contains node values at a given depth, ordered from deepest to root. Ask if nodes within each level should remain left-to-right.

2. Choose an approach

Decide between BFS with level reversal or DFS with depth tracking. BFS is straightforward for level-order; DFS can be more memory-efficient for skewed trees.

3. Implement the traversal

For BFS: use a queue, process level by level, and append each level's values to a result list. For DFS: recursively traverse, passing depth, and append node values to a list at that depth.

4. Reverse the levels

After collecting all levels in top-down order, reverse the list of levels to achieve deepest-to-root order. If using DFS, you can also insert each level at the beginning of the result list.

5. Analyze complexity and edge cases

State time complexity O(n) and space complexity O(n) for BFS (queue) or O(h) for DFS (recursion stack). Discuss edge cases: empty tree, single node, skewed tree.

Key Points to Mention

  • BFS with queue for level-order traversal
  • DFS with depth tracking as alternative
  • Reversing the order of levels
  • Time and space complexity analysis
  • Handling edge cases (empty tree, single node)
  • Clarifying output format with interviewer

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