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Google·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePending
Jun 2026Remote

Summary

Did a phone screen with Google and got a coding question that's basically one of the LeetCode 150. Not identical, but close enough that prepping that list seems worth it.

Questions Asked (1)

Q1

A coding problem similar to a well-known LeetCode problem from the top 150 list.

Algorithms & Data Structures
Author's notes

Not a direct copy but close enough that anyone who drilled that list would recognize it.

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AI HintsAI Generated

Suggested Approach

Clarify the problem, constraints, and edge cases, then discuss brute force and optimize using appropriate data structures or algorithms. Walk through your solution with examples, analyze time and space complexity, and write clean, modular code while explaining your thought process.

Pro tip: Google values structured problem-solving and communication over just getting the right answer. Verbally explain your reasoning, trade-offs, and how you would test and scale your solution.

1. Understand and Clarify

Restate the problem in your own words, ask clarifying questions about input/output, constraints, and edge cases. Confirm assumptions with the interviewer.

2. Explore Approaches

Discuss a brute-force solution first, then identify bottlenecks and propose optimized approaches using appropriate data structures or algorithms. Compare trade-offs.

3. Plan and Code

Outline your chosen approach step-by-step, then write clean, modular code. Use meaningful variable names and handle edge cases explicitly.

4. Test and Debug

Walk through your code with a few test cases, including edge cases. Identify and fix any bugs or logical errors.

5. Analyze and Optimize

State the time and space complexity of your solution. Discuss potential optimizations or alternative approaches if needed.

Key Points to Mention

  • Clarify problem constraints and edge cases before coding
  • Start with a brute-force solution and then optimize
  • Choose the right data structures (e.g., hash maps, heaps, trees) based on trade-offs
  • Analyze time and space complexity using Big-O notation
  • Write clean, modular code with meaningful names
  • Test with examples and edge cases to ensure correctness

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