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Oracle·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Short Oracle SWE interview, just one design question about finding a missing number. Nothing fancy, pretty standard stuff.

Questions Asked (1)

Q1

Given an array of numbers with one missing, find the missing number.

Algorithms & Data Structures
Author's notes

Classic problem, probably should've nailed it without hesitation but I spent a beat overthinking whether they wanted the sum formula or a sort-based approach.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints: is the array a permutation of numbers from 1 to n with one missing, or from 0 to n? Then present the optimal solution using the sum formula (or XOR) to achieve O(n) time and O(1) space, and discuss trade-offs with alternative approaches like sorting or hashing.

Pro tip: Mention that XOR avoids integer overflow issues that can occur with the sum approach when n is large, showing awareness of edge cases and numerical limits.

1. Clarify the problem

Ask questions to confirm the range of numbers (e.g., 1 to n or 0 to n), whether the array is sorted, and if there are any constraints on time or space complexity.

2. Discuss brute force and better approaches

Briefly mention naive solutions like sorting (O(n log n)) or using a hash set (O(n) space), then transition to the optimal approach.

3. Present the optimal solution

Explain the sum formula: expected sum = n*(n+1)/2, actual sum = sum of array, missing = expected - actual. Alternatively, use XOR: XOR all numbers from 1 to n and XOR all array elements; the result is the missing number.

4. Analyze complexity and edge cases

State time complexity O(n) and space O(1). Discuss edge cases like missing number being the first or last, and potential integer overflow with sum (mitigated by XOR).

5. Provide code or pseudocode

Write clean code in a preferred language, handling input validation and explaining each step.

Key Points to Mention

  • Time complexity: O(n) for both sum and XOR approaches.
  • Space complexity: O(1) extra space.
  • Sum formula: n*(n+1)/2 for 1 to n, or n*(n-1)/2 for 0 to n-1.
  • XOR approach: XOR all numbers from 1 to n and XOR all array elements; result is missing number.
  • Integer overflow risk with sum for large n; XOR avoids this.
  • Edge cases: missing number at start or end, array size 1, empty array (if allowed).

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