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Netflix·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jun 2026

Summary

Netflix SWE interview with a sliding window problem dressed up in streaming flavor. Pretty standard underneath the theme.

Questions Asked (1)

Q1

Given a list of show names being streamed in sequence, find the length of the longest contiguous subsequence where no show name repeats.

Algorithms & Data Structures
Author's notes

It's basically the classic sliding window substring problem but with show titles as the elements.

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AI HintsAI Generated

Suggested Approach

Use a sliding window with a hash set to track unique show names, expanding the right pointer and shrinking the left when a duplicate is found. Keep track of the maximum window length seen. This yields O(n) time and O(min(n, m)) space, where m is the number of unique shows.

Pro tip: Clarify edge cases upfront (empty list, all unique, all same) and mention that the solution handles streaming data with a single pass. Also, discuss how you'd adapt if the list is too large to fit in memory.

1. Clarify the problem

Restate the problem in your own words and ask clarifying questions about input size, data types, and expected output. Confirm that 'contiguous subsequence' means a subarray of consecutive elements.

2. Discuss brute force and optimal approach

Mention that a brute force check of all subarrays would be O(n^3) or O(n^2) with a set. Then propose the sliding window with a hash set for O(n) time.

3. Walk through the algorithm

Explain the two-pointer technique: initialize left=0, max_len=0, and an empty set. Iterate right from 0 to n-1; if the show at right is in the set, remove elements from the left until it's not. Add the show at right to the set and update max_len.

4. Analyze complexity and edge cases

State that time complexity is O(n) because each element is added and removed at most once. Space is O(min(n, m)) where m is the number of unique shows. Discuss edge cases: empty list, single element, all duplicates, and all unique.

5. Code and test

Write clean code with meaningful variable names. Test with a few examples, including the edge cases, and trace through the logic to ensure correctness.

Key Points to Mention

  • Sliding window technique with two pointers
  • Hash set for O(1) lookups to detect duplicates
  • Time complexity O(n) and space complexity O(min(n, m))
  • Handling edge cases: empty input, all unique, all same
  • Single-pass streaming suitability
  • Alternative approaches (e.g., using a hash map to store last index) and their trade-offs

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