← Amazon Interview Insights

Amazon·Software Engineer·Online Assessment (OA)·Intermediate

Intermediate
Jun 2026

Summary

Amazon SWE online assessment with a sliding window string problem. Pretty standard stuff for an OA but the streaming framing threw me off a bit at first.

Questions Asked (1)

Q1

Given a string S and a target string T, find all starting indices in S where a substring of length equal to T is an anagram of T.

Algorithms & Data Structures
Author's notes

The streaming angle messed with my head more than it should have.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Use a sliding window of length equal to T's length, and compare character frequency counts between the window and T. Optimize by updating counts incrementally as the window slides, achieving O(n) time.

Pro tip: Mention that you can avoid recomputing the entire frequency array by updating only the characters entering and leaving the window, and use a match counter to track how many characters have the correct frequency.

1. Clarify and Confirm

Restate the problem to ensure understanding: find all starting indices where a substring of S of length |T| is an anagram of T. Confirm edge cases like empty strings or T longer than S.

2. Choose Data Structures

Use frequency arrays (size 26 for lowercase letters) or hash maps to count characters in T and in the current window of S.

3. Sliding Window with Incremental Updates

Initialize the window with the first |T| characters of S. Slide the window one character at a time: remove the leftmost character, add the new rightmost character, and update the frequency counts accordingly.

4. Track Matches Efficiently

Maintain a counter of how many characters have the exact required frequency. When the counter equals the number of distinct characters in T, the current window is an anagram; record its starting index.

5. Analyze Complexity and Test

State time complexity O(n) and space O(1) (since alphabet size is fixed). Walk through a small example to verify correctness, including edge cases.

Key Points to Mention

  • Sliding window technique to avoid redundant computations
  • Frequency counting using arrays or hash maps
  • Incremental update of counts when sliding the window
  • Match counter to achieve O(1) check per window
  • Time complexity O(n) and space complexity O(1) for fixed alphabet
  • Handling edge cases: T longer than S, empty strings, repeated characters

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