Meta·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jun 2026

Summary

Meta SWE coding round with a two-pointer problem that sounds easy until you actually think about the edge cases. Pretty standard algorithmic interview but the follow-up conditions kept it interesting.

Questions Asked (1)

Given a sorted integer array and a target value, find the pair of elements whose sum is closest to the target. Return any valid pair if multiple answers exist. Follow-ups included handling a very large or very small target and what you'd do if the array wasn't sorted.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I went straight for two pointers since the array is sorted, which is the right call.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and constraints, then propose the two-pointer technique for the sorted array, explaining its O(n) time and O(1) space complexity. Discuss how to handle follow-ups: for extreme targets, consider integer overflow and edge cases; for unsorted arrays, compare sorting (O(n log n)) vs. hash map (O(n) time, O(n) space) approaches.

Pro tip: Explicitly state that you're tracking the minimum absolute difference and updating the closest pair when a smaller difference is found, and mention that if the target is very large or small, you might need to use a data type with a wider range or handle overflow carefully.

1. Clarify and Confirm

Ask clarifying questions: Is the array sorted? Can it contain duplicates? What should be returned if no pair exists? Are there memory constraints? Confirm the expected output format.

2. Outline the Optimal Approach

For the sorted array, explain the two-pointer technique: initialize left at 0 and right at n-1, compute sum, update closest pair based on absolute difference, and move pointers inward based on comparison with target.

3. Analyze Complexity and Trade-offs

State time and space complexity: O(n) time, O(1) space. Compare with brute force O(n^2) and binary search O(n log n) approaches, highlighting why two-pointer is optimal for sorted input.

4. Address Follow-ups

For very large/small targets: discuss integer overflow and potential need for long or arbitrary precision. For unsorted array: compare sorting first (O(n log n) time, O(1) space if in-place) vs. using a hash map (O(n) time, O(n) space).

5. Test with Examples

Walk through a simple example (e.g., array [-1, 2, 3, 4], target=3) to demonstrate correctness, and mention edge cases like empty array, single element, or all elements summing to less than target.

Key Points to Mention

Two-pointer technique for sorted arrays: O(n) time, O(1) space.
Tracking minimum absolute difference and updating closest pair.
Handling integer overflow for extreme targets (use long or BigInteger).
For unsorted arrays: sorting first (O(n log n)) vs. hash map (O(n) time, O(n) space).
Edge cases: empty array, single element, duplicates, no valid pair.
Clarifying questions to understand constraints and expected output.

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