Notion·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jul 2026

Summary

Notion Data Engineer interview with a coding question that was more interesting than I expected. The problem sounds like a warmup but the complexity discussion is where they actually wanted to see your thinking.

Questions Asked (1)

Given a string and an integer k, write a function that counts the number of distinct substrings of length exactly k in the string. Walk through your approach, complexity, and edge cases.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

Sliding window plus a hash set, pretty mechanical to implement.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and edge cases, then propose a sliding window approach using a hash set to collect substrings of length k. Analyze time and space complexity, and discuss potential optimizations or trade-offs.

Pro tip: Mention that using a rolling hash can reduce time complexity to O(n) on average, but be prepared to discuss collision handling and when it's worth the added complexity.

1. Clarify requirements and edge cases

Ask about input constraints (e.g., string length, character set) and confirm expected behavior for edge cases like k > string length or k = 0.

2. Outline the sliding window approach

Explain that you'll iterate through the string, extract each substring of length k, and insert it into a hash set to track distinct substrings.

3. Analyze complexity

State that time complexity is O(n * k) due to substring extraction and hashing, and space complexity is O(n * k) in the worst case for storing substrings.

4. Discuss optimizations and trade-offs

Mention that rolling hash can achieve O(n) average time but introduces collision risk; compare with other methods like suffix automaton for different trade-offs.

5. Handle edge cases and test

Walk through examples like k > n (return 0), k = 0 (return 0 or 1 depending on definition), and strings with repeated characters to ensure correctness.

Key Points to Mention

Sliding window technique for extracting substrings of fixed length
Using a hash set to efficiently track distinct substrings
Time complexity O(n*k) and space complexity O(n*k) for the basic approach
Rolling hash optimization to achieve O(n) average time, with collision considerations
Edge cases: k > n, k = 0, empty string, and repeated characters
Trade-offs between simplicity and performance, and when to use more advanced data structures like suffix automaton

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