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Meta·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Meta coding screen for a software engineer role. One algorithmic question, pretty focused on edge case handling and efficiency. Not a lot of back and forth beyond that.

Questions Asked (1)

Q1

Given a sorted array of unique integers and an inclusive range [lower, upper], return all ranges within that interval that are missing from the array. Format single missing numbers as 'a' and consecutive gaps as 'a->b'.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

The core logic clicked pretty fast but I fumbled on the edge cases.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and edge cases, then propose a linear scan that tracks the next expected number and compares it to each array element to identify gaps. For each gap, format it as a single number or a range, and finally check for any missing numbers after the last element up to the upper bound.

Pro tip: Mention that the solution runs in O(n) time and O(1) extra space (excluding output), which is optimal since you must examine each element. Also, handle integer overflow carefully when computing ranges, especially if lower/upper are near integer limits.

1. Clarify and Validate

Confirm that the array is sorted, contains unique integers, and that the range is inclusive. Discuss edge cases such as empty array, no missing numbers, or missing numbers at the boundaries.

2. Design the Algorithm

Use a linear scan with a variable 'next' initialized to 'lower'. For each number in the array, if it is greater than 'next', record the missing range from 'next' to number-1. Then set 'next' to number+1.

3. Handle the Tail

After processing all elements, if 'next' is less than or equal to 'upper', record the missing range from 'next' to 'upper'.

4. Format the Output

For each missing range, if the start equals the end, output the single number as a string; otherwise, output 'start->end'.

5. Analyze Complexity and Trade-offs

State that the time complexity is O(n) and space complexity is O(1) extra (excluding output). Discuss potential alternative approaches like binary search, but explain why linear scan is optimal here.

Key Points to Mention

  • Edge cases: empty array, no missing numbers, missing numbers at the start or end of the range.
  • Time and space complexity: O(n) time, O(1) extra space (output not counted).
  • Correct handling of inclusive bounds and formatting rules (single number vs. range).
  • Potential integer overflow when computing ranges (e.g., if upper is INT_MAX).
  • Comparison with binary search approach: binary search would be O(m log n) where m is number of missing ranges, but linear scan is simpler and optimal for dense arrays.
  • Code clarity: use a helper function to format ranges and avoid off-by-one errors.

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