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

Intermediate
Jun 2026

Summary

Amazon OA for a SWE role. One algorithmic problem about counting subarrays, pretty standard sliding window territory but easy to overthink if you're not warmed up.

Questions Asked (1)

Q1

Given an array of server workloads and an integer difference, count how many contiguous subarrays have a max-min difference exactly equal to that integer.

Algorithms & Data Structures
Author's notes

The example with [2,4,6] and k=2 gives 2, which checks out (subarrays [2,4] and [4,6]).

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AI HintsAI Generated

Suggested Approach

Clarify the problem and constraints, then propose an efficient algorithm using two monotonic deques to maintain the sliding window's max and min. Explain how to count subarrays with difference exactly K by computing counts for difference ≤ K and subtracting counts for difference ≤ K-1.

Pro tip: Mention that the two-pointer sliding window works because the max-min difference is monotonic with respect to window expansion, and explicitly state the time and space complexity (O(n) time, O(n) space) to demonstrate optimization awareness.

1. Clarify the problem and constraints

Ask about array size, possible negative values, and whether the difference can be zero. Confirm that subarrays are contiguous and that we need to count all such subarrays.

2. Define a helper function for difference ≤ K

Design a function that counts subarrays where max-min ≤ K using a sliding window with two deques to track max and min in O(n) time.

3. Use inclusion-exclusion to get exactly K

Compute count(≤ K) - count(≤ K-1) to obtain the number of subarrays with max-min exactly equal to K.

4. Implement the sliding window with deques

Maintain two deques: one decreasing for max, one increasing for min. Expand right pointer, adjust left pointer when difference exceeds K, and add (right - left + 1) to the count.

5. Analyze complexity and test edge cases

State O(n) time and O(n) space. Test with small arrays, all equal elements, K=0, and large K to ensure correctness.

Key Points to Mention

  • Sliding window technique with two pointers
  • Monotonic deques for efficient max/min tracking
  • Inclusion-exclusion principle: count(≤K) - count(≤K-1)
  • Time complexity O(n) and space complexity O(n)
  • Handling edge cases: K=0, negative numbers, empty array
  • Why the window is monotonic: expanding window can only increase or maintain max-min difference

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