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

IntermediatePrefer not to say
Jul 2026Remote

Summary

Amazon OA for a SWE role. One algorithmic problem involving subarray beauty calculations, which sounds deceptively manageable until you're actually staring at it.

Questions Asked (1)

Q1

Given an integer array and a size k, compute the total 'beautiness' of the array, where the beauty of a subarray is the count of indices that are strictly greater than all elements to their right within that subarray. Sum this across all subarrays of size k.

Algorithms & Data Structures
Author's notes

The problem reads cleanly but I wasted time on the naive O(n^2 * k) approach before realizing it was going to time out.

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AI HintsAI Generated

Suggested Approach

Clarify the definition of 'beautiness' and confirm that the beauty of a subarray is the count of elements that are strictly greater than all elements to their right within that subarray. Then propose an efficient algorithm, such as using a monotonic stack to compute the number of right-maximum elements for each subarray of size k, and sum them. Analyze time and space complexity, aiming for O(n) or O(n log n).

Pro tip: Demonstrate awareness of edge cases (e.g., k=1, k=n, duplicate elements) and discuss how to handle them without breaking the algorithm. Also, mention that the problem can be solved by counting contributions of each element as a right-maximum in all subarrays of size k, which often leads to a more elegant solution.

1. Clarify the problem

Restate the definition of 'beautiness' and confirm that the beauty of a subarray is the count of elements that are strictly greater than all elements to their right within that subarray. Ask clarifying questions about input constraints, expected output, and edge cases.

2. Discuss brute-force approach

Mention that a naive solution would iterate over all subarrays of size k, and for each, scan from right to left to count right-maximum elements. This takes O(n*k) time, which may be acceptable for small inputs but not for large n.

3. Propose efficient algorithm

Describe an O(n) or O(n log n) approach. For example, use a monotonic stack to find, for each element, the next greater element to its right. Then, for each element, compute the number of subarrays of size k where it is the right-maximum, and sum these contributions.

4. Analyze complexity and edge cases

State the time and space complexity of the proposed solution. Discuss how to handle edge cases such as k=1, k=n, arrays with duplicates, and negative numbers.

5. Test with examples

Walk through a small example to verify the algorithm, such as array [1,2,3,4] with k=2, and compute the expected output manually to ensure correctness.

Key Points to Mention

  • Definition of 'beautiness' and right-maximum elements
  • Brute-force approach and its O(n*k) time complexity
  • Monotonic stack for finding next greater elements
  • Contribution technique: counting how many subarrays of size k have a given element as right-maximum
  • Time and space complexity analysis (aim for O(n) or O(n log n))
  • Edge cases: k=1, k=n, duplicates, negative numbers

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