Meta·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Apr 2026

Summary

Meta coding screen, one algorithm question, pretty standard stuff but the simplicity of it made me second-guess myself the whole time.

Questions Asked (1)

Given a sorted array of integers, find the smallest missing element.

Algorithms & Data Structures

Author's notes

Looked easy and that made me nervous.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints (e.g., array contains positive integers, missing element must be positive, array may be empty). Then leverage the sorted property to achieve O(log n) time using binary search, comparing the element at mid with its expected value (mid + offset).

Pro tip: Always discuss edge cases like empty array, no missing element in range, and negative numbers; also mention that if the array is not sorted, a hash set or cyclic sort could be used, but since it's sorted, binary search is optimal.

1. Clarify constraints and assumptions

Ask about the range of integers, whether the array can be empty, if duplicates are allowed, and if the missing element must be positive. Confirm that the array is sorted in ascending order.

2. Define the expected value pattern

For a sorted array of distinct integers starting from some base (e.g., 1), the element at index i should be base + i. The first index where arr[i] != base + i indicates the missing element is base + i.

3. Apply binary search

Use binary search to find the smallest index i such that arr[i] != base + i. If no such index exists, the missing element is base + n (where n is the array length).

4. Handle edge cases

Check if the array is empty (return base), if the first element is greater than base (return base), and if all elements match the pattern (return base + n).

5. Analyze complexity and test

State that the time complexity is O(log n) and space is O(1). Walk through a few test cases to verify correctness.

Key Points to Mention

Binary search on the index to find the first mismatch between arr[i] and expected value (base + i).
Time complexity O(log n) and space complexity O(1).
Edge cases: empty array, missing element at the beginning, missing element at the end.
Assumption that array contains distinct integers and is sorted; if duplicates exist, the problem changes.
Alternative approaches: linear scan O(n) or using a hash set O(n) space, but binary search is optimal for sorted arrays.
Clarify the starting value (e.g., 1) and whether the missing element must be positive.

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