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Meta·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
May 2026

Summary

Meta coding screen, got a tree problem that looked easy until I started second-guessing my traversal choice mid-interview.

Questions Asked (1)

Q1

Given a binary tree, return the values of the nodes visible from the right side, ordered top to bottom.

Algorithms & Data Structures
Author's notes

I went with BFS and grabbed the last node at each level.

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AI HintsAI Generated

Suggested Approach

Perform a level-order traversal (BFS) using a queue, and for each level, record the last node's value. Alternatively, use DFS with depth tracking, prioritizing the right child, and record the first node encountered at each depth. Both approaches yield the right side view in O(n) time.

Pro tip: Clarify with the interviewer whether the tree can be empty or have only one node, and mention that the right side view includes nodes that are not necessarily right children but are the rightmost at their depth. This shows attention to edge cases and definition precision.

1. Understand the problem and edge cases

Confirm that the right side view consists of the rightmost node at each depth. Discuss edge cases: empty tree, single node, skewed tree, and nodes that are only visible from the right.

2. Choose an approach

Decide between BFS (level-order) and DFS (pre-order with right-first). BFS is intuitive: process level by level and take the last node. DFS is more space-efficient for deep trees: track depth and record the first node seen at each depth.

3. Implement the algorithm

For BFS: use a queue, iterate level by level, and append the last node's value to the result. For DFS: recursively traverse right subtree first, and if the current depth equals the result size, append the node's value.

4. Analyze complexity and test

State time complexity O(n) and space complexity O(n) for BFS (queue) or O(h) for DFS (recursion stack). Walk through a small example to verify correctness.

Key Points to Mention

  • Level-order traversal (BFS) with queue, taking the last node per level.
  • DFS with depth tracking, prioritizing right child, and recording first node at each depth.
  • Time complexity O(n) and space complexity O(n) for BFS or O(h) for DFS.
  • Handling edge cases: empty tree, single node, skewed tree.
  • Definition of right side view: rightmost node at each depth, not just right children.
  • Comparison of BFS vs DFS trade-offs in terms of code simplicity and space.

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