Google·Software Engineer·Technical Phone Screen·Junior

JuniorPending

Aug 2026

Summary

Did my Google SWE intern loop recently, two coding rounds back to back. Spent a lot of time upfront clarifying and talking through my approach before touching the keyboard, got through most of both problems but ran into some minor snags near the end and used basically all the time on each one. Left wondering if "mostly good" is enough to pass or if you need clean runs on both.

Questions Asked (1)

Given a coding problem, walk through your approach before implementing and then code a working solution within the interview time.

Algorithms & Data Structures

Author's notes

Spent a chunk of time clarifying edge cases and talking through the general approach before writing anything.

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AI HintsAI Generated

Suggested Approach

Start by restating the problem and clarifying constraints and edge cases with the interviewer. Then outline a high-level algorithm with time/space complexity before writing clean, modular code. Finally, test with examples and discuss potential optimizations.

Pro tip: Think out loud continuously and treat the interviewer as a collaborator—ask for hints if stuck, but show you can make progress independently. Always leave a few minutes to review your code for off-by-one errors and edge cases.

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. Plan the Approach

Describe your algorithm at a high level, including data structures and why they are appropriate. Analyze time and space complexity.

3. Implement the Solution

Write clean, well-structured code with meaningful variable names. Modularize if helpful, and handle edge cases explicitly.

4. Test and Debug

Walk through your code with a few test cases, including edge cases. Fix any bugs and verify correctness.

5. Optimize and Discuss

If time permits, discuss potential optimizations or alternative approaches. Reflect on trade-offs and scalability.

Key Points to Mention

Clarify input constraints (e.g., size, range, duplicates) and expected output format.
Choose appropriate data structures (e.g., hash map, heap, two pointers) and justify their use.
Analyze time and space complexity of your solution and compare with alternatives.
Handle edge cases such as empty input, single element, or large values.
Write modular, readable code with comments for clarity.
Test with examples and discuss potential optimizations or trade-offs.

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