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Meta·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Meta SWE coding round with a tree problem. Pretty standard algorithmic stuff but the constraint tripped me up more than I expected.

Questions Asked (1)

Q1

Given a binary tree, determine whether every node's value equals the average of all its descendant nodes' values.

Algorithms & Data Structures
Author's notes

I jumped straight to a brute force where I recomputed the subtree sum at every node separately.

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AI HintsAI Generated

Suggested Approach

Use a post-order traversal to compute the sum and count of descendants for each node, then check if the node's value equals the average. Return both the sum and count to the parent to avoid redundant computations. Handle edge cases like leaf nodes (no descendants) and null nodes appropriately.

Pro tip: Clarify with the interviewer whether leaf nodes (with no descendants) should be considered as satisfying the condition vacuously or if they should be excluded. This shows attention to detail and avoids ambiguity.

1. Clarify the problem and edge cases

Ask about the definition of 'descendant' (all nodes in the subtree excluding the node itself) and how to handle leaf nodes and empty trees. Confirm whether the average is computed as sum/count and if integer division is acceptable.

2. Design a recursive post-order traversal

Define a helper function that returns the sum of all node values in the subtree and the number of nodes. For each node, first recursively process left and right children, then compute the average of descendants (excluding the node) and compare with the node's value.

3. Implement the recursion with early termination

In the helper, if any subtree violates the condition, propagate a failure flag. For a leaf node, there are no descendants, so decide based on clarification whether it's valid. Return the sum and count up the tree.

4. Analyze time and space complexity

Explain that the algorithm visits each node once, so time complexity is O(n) where n is the number of nodes. Space complexity is O(h) for the recursion stack, where h is the tree height, which is O(n) in the worst case.

5. Test with examples and edge cases

Walk through a simple tree, a tree with a violation, a single-node tree, and an empty tree. Verify that the logic correctly handles these cases and discuss potential pitfalls like integer division or floating-point precision.

Key Points to Mention

  • Post-order traversal to compute subtree sums and counts bottom-up.
  • Avoiding redundant computations by returning aggregate data from recursive calls.
  • Handling leaf nodes and empty trees as special cases.
  • Time complexity O(n) and space complexity O(h).
  • Using integer arithmetic carefully to avoid precision issues when comparing averages.
  • Early termination if a violation is found to optimize performance.

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