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Meta·Software Engineer·Onsite - Coding / Algorithms·Intermediate

IntermediatePrefer not to say
Jun 2026

Summary

Meta SWE coding round, one tree problem the whole time. Pretty focused session, they wanted to see clean recursive thinking more than anything else.

Questions Asked (1)

Q1

Given an N-ary tree and two nodes p and q, find their lowest common ancestor. If no common ancestor exists, return null.

Algorithms & Data Structures
Author's notes

I knew the binary LCA problem cold so I figured this was the same thing.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints (e.g., whether nodes are guaranteed to be in the tree, if parent pointers exist) and then propose a recursive post-order traversal that returns the LCA if found. If parent pointers are available, consider an alternative approach using a hash set to track ancestors of one node and then traverse from the other.

Pro tip: Always discuss trade-offs: the recursive approach uses O(H) stack space (H = height) and O(N) time, while the parent-pointer approach uses O(N) space but can be more intuitive. Mention that handling the 'no common ancestor' case requires checking if both nodes are actually in the tree.

1. Clarify requirements and constraints

Ask if nodes are guaranteed to be in the tree, if parent pointers are available, and if the tree is static. This determines the approach and edge cases.

2. Choose an approach

If parent pointers exist, use a hash set to store ancestors of p, then traverse from q upward until a common ancestor is found. Otherwise, use a recursive post-order traversal that returns the LCA if both nodes are found in the subtree.

3. Handle edge cases

Consider cases where p or q is the root, where one is an ancestor of the other, or where either node is not present in the tree. Ensure the solution returns null if no common ancestor exists.

4. Implement and test

Write clean code with clear variable names. Walk through a small example to verify correctness, and discuss time and space complexity.

5. Optimize if needed

If the tree is very deep, consider an iterative approach to avoid stack overflow. If multiple queries are expected, discuss preprocessing (e.g., binary lifting) for faster LCA queries.

Key Points to Mention

  • Time and space complexity: O(N) time and O(H) space for recursion, or O(N) space for parent-pointer approach.
  • Handling the case where no common ancestor exists: need to verify both nodes are in the tree.
  • Difference between N-ary tree and binary tree: children are a list, so iterate over all children.
  • Recursive post-order traversal: return the node if it matches p or q, otherwise combine results from children.
  • Parent-pointer approach: use a hash set to store ancestors of one node, then traverse from the other.
  • Edge cases: p or q is root, one is ancestor of the other, or nodes not present.

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