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Amazon·Software Engineer·Online Assessment (OA)·Intermediate

Intermediate
Apr 2026

Summary

Amazon SWE coding round with a geometry-heavy simulation problem. The diagonal traversal angle was a bit unexpected and took some time to wrap my head around.

Questions Asked (1)

Q1

Given n servers on an infinite 2D plane and a sequence of directional redirects (NE, SE, NW, SW), simulate a traversal starting from the first server. Each redirect moves to the nearest unvisited server along the corresponding diagonal ray. If no such server exists, skip the step. Return the final server coordinates after processing all redirects.

Algorithms & Data StructuresSystem Design
Author's notes

The diagonal constraint is what trips you up at first.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and edge cases, then propose an efficient algorithm using spatial indexing (e.g., sorting by x+y and x-y) to quickly find the nearest unvisited server along each diagonal. Simulate the traversal step-by-step, updating visited servers and handling skips, and finally return the last visited server's coordinates.

Pro tip: Demonstrate awareness of real-world scalability by discussing how to handle large n and many redirects, and mention potential optimizations like balanced trees or hash maps for diagonal groups.

1. Clarify requirements and edge cases

Ask about input format, constraints (n, number of redirects), and edge cases such as no unvisited server in a direction or multiple servers at the same distance.

2. Choose data structures for efficient lookup

Group servers by their diagonal lines (x+y for NE/SW, x-y for NW/SE) and sort each group to enable binary search for the nearest unvisited server.

3. Simulate traversal with visited tracking

Start at the first server, mark it visited, and for each redirect, find the nearest unvisited server in the specified direction; if none, skip the step.

4. Analyze complexity and optimize

Discuss time and space complexity, and propose optimizations like using balanced BSTs or lazy deletion to handle visited servers efficiently.

5. Return final coordinates and test

After processing all redirects, return the coordinates of the last visited server, and walk through a small example to verify correctness.

Key Points to Mention

  • Diagonal grouping using x+y and x-y to map servers to NE/SW and NW/SE lines.
  • Sorting each diagonal group to enable binary search for nearest neighbor.
  • Visited tracking with efficient removal or lazy deletion to avoid revisiting.
  • Handling skips when no unvisited server exists in the given direction.
  • Time complexity analysis: O(n log n) preprocessing and O(log n) per redirect.
  • Edge cases: multiple servers on same diagonal, collinear points, and starting server inclusion.

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