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Amazon·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Amazon SWE coding round, one algorithmic question about arrays. Pretty short session, nothing behavioral.

Questions Asked (1)

Q1

Given two integer arrays, find their longest common prefix.

Algorithms & Data Structures
Author's notes

Not the string version you always prep for, which threw me off for a second.

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AI HintsAI Generated

Suggested Approach

First, clarify the problem definition: confirm whether 'longest common prefix' refers to the longest sequence of elements that appear at the beginning of both arrays in the same order. Then, propose an efficient algorithm that compares elements from the start until a mismatch is found, and discuss time and space complexity.

Pro tip: At Amazon, interviewers value candidates who proactively consider edge cases and scalability. Mention how your solution handles large arrays and whether it can be optimized for early termination.

1. Clarify the problem

Ask the interviewer to confirm the definition: is it the longest sequence of elements that are identical and appear at the start of both arrays? Also clarify if the arrays can be empty or have different lengths.

2. Discuss brute force and optimal approach

Start with a simple brute force: compare elements one by one until a mismatch. Then, note that this is already optimal for this problem, as you must examine each element until the first difference.

3. Analyze complexity

State that the time complexity is O(min(n, m)) where n and m are the lengths of the arrays, and space complexity is O(1) if you only return the length or O(k) if you return the prefix array, where k is the length of the prefix.

4. Handle edge cases

Discuss edge cases: empty arrays, arrays with no common prefix, one array being a prefix of the other, and arrays of different lengths.

5. Write code and test

Implement the solution in a clean, readable manner, and walk through a few test cases to verify correctness.

Key Points to Mention

  • Definition of longest common prefix for arrays (sequence of elements at the start).
  • Time complexity: O(min(n, m)) and why it's optimal.
  • Space complexity: O(1) if returning length, O(k) if returning the prefix array.
  • Edge cases: empty arrays, no common prefix, one array is prefix of the other.
  • Early termination when a mismatch is found.
  • Potential variations: if arrays are sorted or if we need to find common prefix among multiple arrays.

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