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Meta·Software Engineer·Onsite - Coding / Algorithms·Intermediate

Intermediate
May 2026

Summary

Meta SWE coding round with a sliding window / two-pointer problem that required both a working solution and a complexity analysis on the spot. Pretty standard algorithmic interview but the requirement to also write test cases with large inputs added a bit of pressure.

Questions Asked (1)

Q1

Given an integer array and an integer k, find the minimum length subarray where the difference between the maximum and minimum values is at least k. Implement the function, analyze its time complexity, and provide at least three test cases including arrays up to length 10^5.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

The core idea clicked pretty fast for me, you want a sliding window but maintaining the running min and max efficiently is where it gets annoying.

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AI HintsAI Generated

Suggested Approach

Clarify the problem and constraints, then propose an efficient solution using a sliding window with two monotonic deques to track min and max in O(n) time. Walk through the algorithm, analyze complexity, and provide test cases including edge cases and large inputs.

Pro tip: Mention that a naive O(n^2) approach is too slow for n=10^5, and emphasize that the monotonic deque solution is optimal because each element is added and removed at most once. Also, proactively discuss how to handle duplicates and negative numbers.

1. Clarify requirements and constraints

Confirm the definition of subarray (contiguous), the condition (max - min >= k), and the expected input size (up to 10^5). Ask about edge cases like k <= 0 or no valid subarray.

2. Propose an efficient algorithm

Describe a sliding window approach with two monotonic deques to maintain the min and max of the current window. Explain how to expand the right pointer and shrink the left pointer when the condition is met.

3. Analyze time and space complexity

State that each element is added and removed from each deque at most once, giving O(n) time. Space is O(n) for the deques in the worst case.

4. Provide test cases

Include at least three test cases: a small array with a valid subarray, an array with no valid subarray, and a large array of length 10^5 (e.g., random or increasing) to demonstrate efficiency.

5. Discuss trade-offs and edge cases

Mention alternative approaches (e.g., sorting, binary search) and why they are less efficient. Address edge cases like k <= 0, empty array, and all elements equal.

Key Points to Mention

  • Sliding window technique with two monotonic deques for O(n) time
  • Handling duplicates and negative numbers in the deques
  • Time complexity: O(n) because each element is processed at most twice
  • Space complexity: O(n) for the deques
  • Edge cases: k <= 0, no valid subarray, array length 1
  • Test cases including a large array of size 10^5 to validate performance

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