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Google·Software Engineer·Technical Phone Screen·Intermediate

IntermediateRejected
Apr 2026

Summary

Google SWE interview, one coding question that turned into a slow-motion disaster. The interviewer was patient and kept nudging me toward a solution but I still couldn't get there.

Questions Asked (1)

Q1

Given a definition of 'Perfect Wake Numbers', count how many such numbers exist from 1 to n.

Algorithms & Data Structures
Author's notes

This was a follow-up to an earlier problem and I just fell apart.

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AI HintsAI Generated

Suggested Approach

First, clarify the definition of 'Perfect Wake Numbers' and any constraints (e.g., n up to 10^9). Then, derive a mathematical characterization or efficient algorithm (e.g., digit DP, precomputation, or formula) to count them up to n, and analyze time/space complexity.

Pro tip: Always ask clarifying questions about the definition and constraints before diving into a solution; this shows you think about edge cases and scalability, which is crucial at Google.

1. Clarify the definition and constraints

Ask the interviewer to precisely define 'Perfect Wake Numbers' and provide examples. Also, inquire about the range of n and expected time/space complexity.

2. Explore small cases and identify patterns

Manually compute or write a brute-force check for small n to understand the properties of these numbers. Look for patterns or mathematical relationships.

3. Derive an efficient counting method

Based on the pattern, design an algorithm (e.g., digit DP, combinatorial counting, or precomputation) that can count up to n without iterating over all numbers if n is large.

4. Analyze complexity and optimize

Determine the time and space complexity of your approach. If needed, optimize further by reducing states or using mathematical shortcuts.

5. Test with edge cases and discuss

Validate your solution with edge cases (n=0, n=1, large n) and explain how you would test it. Be ready to discuss trade-offs.

Key Points to Mention

  • Clarification of the problem definition and constraints
  • Brute-force approach for small n to understand the problem
  • Pattern recognition and mathematical characterization
  • Digit DP or combinatorial counting for large n
  • Time and space complexity analysis
  • Edge cases and testing strategy

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