Amazon·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026

Summary

Amazon SWE interview focused entirely on a binary tree visibility problem. They wanted two full implementations plus complexity analysis and edge case walkthroughs, so it was more thorough than I expected for what sounded like a single question.

Questions Asked (1)

Given a binary tree, return the left view and right view: for each level, the leftmost and rightmost visible node. Implement both a BFS level-order approach and a DFS approach with depth tracking, and provide time and space complexity for each.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I started with BFS because it felt more natural for level-order stuff, and that part went fine.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the definition of left/right view and edge cases, then present both BFS and DFS solutions with clear code and complexity analysis. Emphasize the trade-offs between the two approaches and how they can be adapted to variations.

Pro tip: Mention that the left view can be obtained by swapping left and right children in the DFS traversal, and highlight that BFS naturally handles level boundaries while DFS uses depth tracking—this shows deep understanding.

1. Clarify the problem

Confirm that left/right view means the first/last node at each level from left to right. Discuss edge cases: empty tree, single node, skewed tree.

2. BFS approach

Use a queue to process nodes level by level. For each level, record the first node (left view) and last node (right view).

3. DFS approach

Traverse recursively, passing depth. For left view, visit left child first; for right view, visit right child first. Record the first node seen at each depth.

4. Complexity analysis

Both approaches visit each node once: O(n) time. Space: BFS O(w) where w is max width; DFS O(h) for recursion stack, where h is height.

5. Discuss trade-offs

Compare BFS (intuitive, level-based) vs DFS (less memory for skewed trees, easy to modify for variations). Mention iterative vs recursive DFS.

Key Points to Mention

Definition of left/right view: first/last node per level.
BFS uses queue and processes level by level; track level size.
DFS uses preorder traversal with depth parameter; maintain a result array indexed by depth.
Time complexity O(n) for both; space complexity O(w) for BFS and O(h) for DFS.
Edge cases: empty tree, single node, skewed tree.
Trade-offs: BFS may use more memory for wide trees; DFS may risk stack overflow for deep trees.

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