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

Intermediate
Jul 2026

Summary

Amazon SWE coding round with a classic dynamic programming problem. Nothing too surprising but the constraints are real so a naive solution will time out.

Questions Asked (1)

Q1

Given an array of bar heights, compute the total amount of rainwater that can be trapped between the bars.

Algorithms & Data Structures
Author's notes

Classic problem but I still fumbled the first few minutes trying to remember whether to use the two-pointer approach or precompute prefix/suffix max arrays.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and walking through a small example to ensure understanding. Then present a solution using precomputed max heights from left and right, explaining how water at each index is determined by the minimum of these maxima minus the bar height. Finally, discuss time and space complexity and possible optimizations.

Pro tip: Mention the two-pointer approach as an O(1) space optimization, but only after presenting the straightforward O(n) space solution. This shows you can balance clarity and efficiency, which Amazon values.

1. Clarify and Confirm

Ask clarifying questions about input constraints, edge cases (e.g., empty array, negative heights), and expected output format. Confirm that water can be trapped only between bars, not outside.

2. Walk Through Example

Choose a small array like [0,1,0,2,1,0,1,3,2,1,2,1] and manually compute trapped water to demonstrate understanding and validate your approach.

3. Explain the Algorithm

Describe how to precompute left_max and right_max arrays, then iterate to sum min(left_max[i], right_max[i]) - height[i] for each index. Emphasize that water at each position is limited by the shorter of the two tallest bars on either side.

4. Analyze Complexity

State that the precomputation approach takes O(n) time and O(n) space. Mention that the two-pointer technique can reduce space to O(1) while maintaining O(n) time.

5. Discuss Edge Cases and Optimizations

Cover edge cases like empty array, single bar, or strictly increasing/decreasing heights. Optionally, outline the two-pointer algorithm to show depth.

Key Points to Mention

  • Water trapped at index i = min(max_left[i], max_right[i]) - height[i]
  • Precompute left_max and right_max arrays in O(n) time
  • Two-pointer approach for O(1) space optimization
  • Time complexity O(n), space complexity O(n) for basic solution
  • Edge cases: empty array, single element, all bars same height
  • Amazon leadership principles: customer obsession (clarify requirements), dive deep (explain algorithm)

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