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Meta·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
May 2026

Summary

Meta SWE coding round, one algorithmic question about finding a unique element in an array with a constraint on extra space. Pretty lean session, just the one problem but the follow-up on space complexity is where things get interesting.

Questions Asked (1)

Q1

Given an array where all elements appear more than once except one, find the unique element using minimal extra space.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

My first instinct was a hash map and I almost said it out loud before catching myself.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., array size, element range, whether elements appear exactly twice or more than twice) and then propose the XOR-based solution that finds the unique element in O(n) time and O(1) extra space. Explain why XOR works: pairs cancel out, leaving the unique element. If the problem allows elements to appear more than twice, discuss alternative approaches like bit manipulation with counters or hash maps, but emphasize the XOR solution as optimal for the common case.

Pro tip: Mention that XOR is both commutative and associative, so the order doesn't matter, and that it's a classic trick for finding the odd-one-out. Also, note that this approach works in-place and is highly efficient, which is crucial for large datasets.

1. Clarify the problem

Ask whether all elements appear exactly twice except one, or if they can appear more than twice. Also confirm if the array is mutable and if there are any constraints on time or space.

2. Propose the XOR solution

Explain that XORing all elements together will cancel out duplicates (since x ^ x = 0) and leave the unique element (since x ^ 0 = x). This uses O(1) extra space and O(n) time.

3. Discuss edge cases and alternatives

If elements can appear more than twice, XOR alone won't work. Mention alternatives like using a hash map (O(n) space) or bitwise counters (O(1) space but more complex).

4. Analyze trade-offs

Compare the XOR approach with other methods (e.g., sorting, hash map) in terms of time and space complexity, emphasizing the minimal extra space requirement.

5. Conclude with the optimal solution

Reiterate that for the common case (all elements appear exactly twice except one), XOR is optimal. Provide a quick code snippet or pseudocode to illustrate.

Key Points to Mention

  • XOR properties: x ^ x = 0, x ^ 0 = x, commutative and associative
  • Time complexity: O(n) single pass
  • Space complexity: O(1) extra space
  • Handling elements appearing more than twice: need different approach (e.g., bitwise counters or hash map)
  • In-place operation and no additional data structures
  • Potential follow-up: what if there are two unique elements? (XOR all, find rightmost set bit, partition array)

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