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Google·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
May 2026

Summary

Google coding interview, one question about binary strings. Pretty algorithmic, felt like a dynamic programming setup once I stopped overthinking it.

Questions Asked (1)

Q1

Given a number N, find all N-digit binary strings that contain no two consecutive 1s.

Algorithms & Data Structures
Author's notes

Took me a minute to see the structure.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and edge cases, then propose a backtracking solution that builds the string character by character, pruning branches that would create consecutive 1s. Discuss the time complexity and possible optimizations, such as using dynamic programming to count or generate strings efficiently.

Pro tip: Mention that the number of valid strings follows the Fibonacci sequence, which can impress the interviewer and lead to a discussion on using DP for counting or generating strings. Also, consider asking whether the output should be returned as a list or printed, and whether N can be zero.

1. Clarify requirements and edge cases

Ask about input constraints (e.g., N >= 0), output format (list of strings, print, etc.), and whether the solution should be recursive or iterative. Confirm that 'no two consecutive 1s' means no substring '11'.

2. Outline a backtracking approach

Explain that you can build the string position by position, tracking the last character. At each step, you can append '0' always, and append '1' only if the last character was not '1'. This prunes invalid branches early.

3. Analyze complexity and optimizations

State that the number of valid strings is Fibonacci(N+2), so the time complexity is O(Fib(N)) which is exponential in N. Mention that for large N, generating all strings is infeasible, but for counting, DP can be used.

4. Discuss alternative approaches

Mention that you could also use dynamic programming to count the number of valid strings, or generate them using a recursive function that returns a list of strings. Compare trade-offs.

5. Code and test

Write clean code (e.g., in Python) with a recursive helper function. Test with small N (e.g., N=1,2,3) and edge cases like N=0.

Key Points to Mention

  • Backtracking with pruning to avoid consecutive 1s
  • Time complexity is exponential, specifically O(Fibonacci(N))
  • The count of valid strings follows the Fibonacci sequence
  • Dynamic programming can be used for counting or generating efficiently
  • Edge cases: N=0 (empty string), N=1 (0,1)
  • Space complexity: O(N) for recursion stack, plus output storage

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