Apple·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Apr 2026

Summary

Apple data engineer interview with a coding question focused on finding duplicates. Not much context to go on, but it reads like a technical screen.

Questions Asked (1)

Given a dataset or array, find all duplicate values.

Algorithms & Data Structures

Author's notes

Classic problem but Apple has a way of making you second-guess the obvious solution.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., data type, size, memory limits, whether the array is sorted). Then discuss multiple solutions with trade-offs, such as using a hash set for O(n) time and O(n) space, or sorting for O(n log n) time and O(1) extra space. Finally, present code for the optimal solution and analyze its complexity.

Pro tip: At Apple, interviewers value clean, efficient code and the ability to discuss trade-offs. Always ask clarifying questions before diving into a solution, and be prepared to optimize for either time or space based on the constraints.

1. Clarify the problem

Ask about input characteristics: data type, size, sortedness, memory constraints, and expected output format (e.g., list of duplicates, counts, or unique duplicates).

2. Discuss approaches

Outline multiple solutions: brute force (O(n^2)), hash set (O(n) time, O(n) space), sorting (O(n log n) time, O(1) space), and in-place marking if values are within a range.

3. Choose and implement

Select the most appropriate approach based on constraints, then write clean, bug-free code with meaningful variable names and edge-case handling.

4. Analyze complexity

State the time and space complexity of your solution and compare it to alternatives, explaining why your choice is optimal for the given scenario.

5. Test with examples

Walk through the code with sample inputs, including edge cases like empty array, no duplicates, all duplicates, and large inputs.

Key Points to Mention

Time and space complexity trade-offs between hash set and sorting approaches
Handling edge cases: empty array, single element, no duplicates, all duplicates
Using a hash set to track seen elements and collect duplicates
In-place marking technique if array values are within a known range (e.g., 1 to n)
Sorting the array first to bring duplicates together, then scanning for adjacent equals
Clarifying whether the output should contain each duplicate once or multiple times

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