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Amazon·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jul 2026

Summary

Amazon SWE coding round, one question, sliding window stuff. Pretty standard if you've done any array problems before.

Questions Asked (1)

Q1

Given a binary array where each element is 1 (server ON) or 0 (server OFF), and an integer k representing the max number of OFF servers you can flip ON, find the length of the longest contiguous subarray that can be made all ON.

Algorithms & Data Structures
Author's notes

It's basically max consecutive ones with flips, just dressed up in a server theme.

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AI HintsAI Generated

Suggested Approach

Use a sliding window technique to maintain a window with at most k zeros, expanding the right pointer and shrinking the left when zeros exceed k. Track the maximum window length seen. This yields an O(n) time, O(1) space solution.

Pro tip: Clarify that the problem is equivalent to finding the longest subarray with at most k zeros, and mention that the window never needs to shrink below the current maximum length, which simplifies the code.

1. Understand the problem

Restate the problem: find the longest contiguous subarray that can be made all 1s by flipping at most k zeros. Confirm with the interviewer that flipping means changing 0 to 1.

2. Choose the right technique

Recognize this as a sliding window problem because we need the longest subarray satisfying a constraint (at most k zeros). Explain why brute force is inefficient.

3. Implement sliding window

Initialize left and right pointers, a zero count, and max length. Expand right, increment zero count if element is 0. While zero count > k, move left and decrement zero count if element is 0. Update max length.

4. Analyze complexity

State that each element is visited at most twice, so time complexity is O(n) and space complexity is O(1).

5. Test with examples

Walk through a small example, e.g., [1,0,1,0,1], k=1, to verify the algorithm returns 3. Also consider edge cases like all zeros or k >= number of zeros.

Key Points to Mention

  • Sliding window technique for O(n) time complexity
  • Maintaining a count of zeros within the window
  • Shrinking the window when zeros exceed k
  • Tracking the maximum window length
  • Handling edge cases: k=0, all ones, all zeros, k >= total zeros
  • Space complexity O(1) with two pointers

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