Salesforce·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Apr 2026

Summary

Salesforce software engineer interview with a classic array problem. Nothing too wild, but the space constraint is where people trip up if they haven't seen it before.

Questions Asked (1)

Given an array of n distinct numbers covering the range [0, n] with exactly one value missing, find the missing number in O(n) time using O(1) extra space.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The O(1) space requirement is the part that filters people out.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints and edge cases, then propose using the mathematical property that the sum of numbers from 0 to n is n(n+1)/2. Subtract the sum of the array elements from this expected sum to find the missing number, achieving O(n) time and O(1) space.

Pro tip: Mention that while the sum approach is straightforward, it can cause integer overflow for large n; you can avoid this by using XOR instead, which is also O(n) time and O(1) space and avoids overflow.

1. Clarify the problem

Confirm that the array contains n distinct numbers from 0 to n with exactly one missing, and that the goal is to find it in O(n) time and O(1) extra space.

2. Discuss naive approaches

Briefly mention that sorting or using a hash set would work but violate the time or space constraints, showing you understand trade-offs.

3. Propose the sum-based solution

Explain that the sum of 0..n is n(n+1)/2, and the missing number is expectedSum - actualSum. Walk through a small example to illustrate.

4. Address potential overflow

Acknowledge that the sum can overflow for large n, and present XOR as an alternative: XOR all numbers from 0 to n and all array elements; the result is the missing number.

5. Analyze complexity and edge cases

State that both approaches run in O(n) time and O(1) space. Discuss edge cases like n=0, missing number at boundaries, and large n.

Key Points to Mention

Time complexity O(n) and space complexity O(1) for both sum and XOR methods.
Mathematical formula for sum of 0 to n: n(n+1)/2.
XOR properties: a ^ a = 0, a ^ 0 = a, and XOR is commutative and associative.
Integer overflow risk with sum method for large n, and how XOR avoids it.
Edge cases: n=0 (array empty, missing 0), missing number at start or end.
Trade-offs: sum is simpler but may overflow; XOR is robust but slightly less intuitive.

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