← Meta Interview Insights

Meta·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Meta SWE coding round, tree traversal question. Pretty standard stuff but the dual-view twist made me think twice about how I was structuring my BFS.

Questions Asked (1)

Q1

Given the root of a binary tree, return both the left side view and the right side view (the leftmost and rightmost node at each level, top to bottom).

Algorithms & Data Structures
Author's notes

I jumped straight to BFS which was fine, but I got a little tangled trying to return both views in one pass.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Use BFS level-order traversal to process nodes level by level, recording the first and last node at each level for left and right views respectively. Alternatively, use DFS with depth tracking, updating the left view when visiting a level for the first time and the right view when visiting from the right side first. Clearly explain the chosen approach, its time and space complexity, and handle edge cases like an empty tree.

Pro tip: Mention that both views can be obtained in a single traversal by tracking the first and last nodes per level, and discuss the trade-offs between BFS and DFS in terms of code simplicity and memory usage.

1. Clarify the problem and edge cases

Confirm that the views are from top to bottom, and discuss handling of an empty tree or single-node tree. Ask if the tree is balanced or if there are constraints on node values.

2. Choose an approach

Decide between BFS (level-order traversal) and DFS (pre-order with depth tracking). Explain why one might be preferred, e.g., BFS naturally processes levels in order.

3. Outline the algorithm

For BFS: use a queue, process each level, record the first and last node values. For DFS: traverse left-first for left view and right-first for right view, using a depth parameter to know when to add a node.

4. Analyze complexity and optimize

State that both approaches run in O(n) time and O(n) space in the worst case (queue or recursion stack). Mention that BFS may use O(w) space where w is max width, while DFS uses O(h) where h is height.

5. Test with examples

Walk through a small example (e.g., a tree with 3 levels) to verify the algorithm produces correct left and right views. Consider edge cases like skewed trees.

Key Points to Mention

  • Level-order traversal (BFS) using a queue to process nodes level by level.
  • DFS with depth tracking: left view via pre-order (root, left, right), right view via reverse pre-order (root, right, left).
  • Time complexity O(n) and space complexity O(n) for both approaches, with nuances (BFS: O(w), DFS: O(h)).
  • Handling edge cases: empty tree returns empty lists, single node appears in both views.
  • Possibility of combining both views in a single traversal to save time.
  • Trade-offs between BFS and DFS in terms of code readability and memory usage.

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