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Meta·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Meta coding screen, just one question about binary trees. Pretty short session, nothing too wild.

Questions Asked (1)

Q1

Given a binary tree, determine whether it is height-balanced.

Algorithms & Data Structures
Author's notes

Classic recursion problem but I kept second-guessing myself on what counts as balanced.

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AI HintsAI Generated

Suggested Approach

Clarify the definition of height-balanced (typically, for every node, the heights of left and right subtrees differ by at most 1). Then propose a post-order DFS that returns the height of each subtree and a boolean indicating balance, computing both in a single pass to achieve O(n) time. If needed, discuss the naive O(n^2) approach and why it's suboptimal.

Pro tip: Mention that you can avoid repeated height calculations by returning a sentinel value (e.g., -1) when an imbalance is detected, allowing early termination. This shows you understand optimization and can handle edge cases efficiently.

1. Clarify the problem

Confirm the definition of height-balanced: for every node, the height difference between left and right subtrees is at most 1. Also clarify input/output expectations and edge cases (empty tree, single node).

2. Discuss naive approach

Explain a straightforward solution: for each node, compute the height of left and right subtrees recursively, and check the balance condition. Note that this is O(n^2) due to repeated height computations.

3. Propose optimized approach

Describe a post-order DFS that returns the height of the subtree and a boolean indicating whether it's balanced. Alternatively, return -1 if unbalanced to short-circuit. This achieves O(n) time and O(h) space.

4. Walk through an example

Trace the algorithm on a small tree (e.g., a balanced tree and an unbalanced one) to demonstrate correctness and how early termination works.

5. Analyze complexity and edge cases

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

Key Points to Mention

  • Definition of height-balanced: for every node, |height(left) - height(right)| <= 1.
  • Naive approach: O(n^2) time due to repeated height calculations.
  • Optimized approach: post-order DFS returning height and balance status in one pass.
  • Use of sentinel value (e.g., -1) to indicate imbalance and enable early termination.
  • Time complexity: O(n) because each node is visited once.
  • Space complexity: O(h) for recursion stack, where h is tree height.

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