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18. Single Number

easyAsked at Snowflake

Find the one number in an array where every other appears twice. Snowflake asks this because the XOR trick is exactly the same primitive used to construct erasure-coded data: cheap, commutative, parallel-friendly.

By Alex Chen, Founder, InterviewChamp.AI · Last verified

Source citations

Public interview reports confirming this problem appears in Snowflake loops.

  • Glassdoor (2026-Q1)— Snowflake storage team uses this to set up an erasure-coding follow-up.
  • LeetCode Discuss (2025-11)— Recurring at Snowflake new-grad screens.

Problem

Given a non-empty array of integers nums, every element appears twice except for one. Find that single one. You must implement a solution with a linear runtime complexity and use only constant extra space.

Constraints

  • 1 <= nums.length <= 3 * 10^4
  • -3 * 10^4 <= nums[i] <= 3 * 10^4
  • Each element in the array appears twice except for one element which appears only once.

Examples

Example 1

Input
nums = [2,2,1]
Output
1

Example 2

Input
nums = [4,1,2,1,2]
Output
4

Approaches

1. Hash map counts

Count occurrences; return the key with count 1.

Time
O(n)
Space
O(n)
function singleNumber(nums) {
  const count = new Map();
  for (const n of nums) count.set(n, (count.get(n) || 0) + 1);
  for (const [k, v] of count) if (v === 1) return k;
}

Tradeoff: Violates the O(1) space requirement. Mention only to acknowledge.

2. XOR all elements (optimal)

x XOR x = 0 and x XOR 0 = x. XOR-ing every element cancels duplicates, leaving only the single.

Time
O(n)
Space
O(1)
function singleNumber(nums) {
  let acc = 0;
  for (const n of nums) acc ^= n;
  return acc;
}

Tradeoff: O(1) space, parallelizable (XOR is commutative + associative), perfect for SIMD or partitioned reduction.

Snowflake-specific tips

Snowflake interviewers love this one because the XOR insight is the same primitive used in RAID and erasure coding — both rely on XOR's self-inverse property. Bonus signal: discuss how this aggregates across partitions: each compute node XORs its slice, then a reduce step XORs the per-partition results — no central coordinator needed.

Common mistakes

  • Using sum and subtracting expected duplicates — only works if you know all values up front.
  • Sorting first — O(n log n), violates the linear constraint.
  • Worrying about overflow with XOR — there isn't any.

Follow-up questions

An interviewer at Snowflake may pivot to one of these next:

  • Single Number II (LC 137) — every other appears three times.
  • Single Number III (LC 260) — two singles among duplicates.
  • How does erasure coding use XOR?

Solve it now

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Output

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FAQ

Why does XOR work here?

XOR is commutative and associative, so order doesn't matter. x XOR x = 0, and 0 XOR x = x. So pairs cancel out and only the single survives.

How does Snowflake use XOR in storage?

Reed-Solomon / erasure coding uses XOR-like operations over a finite field. The same self-inverse property lets you reconstruct a lost data block from the others plus a parity block.

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