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Stripe·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Stripe SWE interview with a debugging-round format where instead of writing code from scratch, you're handed broken or inefficient code and have to talk through what's wrong and how to fix it. Less about raw implementation and more about whether you can reason out loud under pressure.

Questions Asked (1)

Q1

You're given a piece of buggy or poorly optimized code. Walk through what's wrong with it, propose a fix, and explain whether your fix is actually optimal.

Algorithms & Data StructuresTechnical Trade-offsRoot Cause Analysis
Author's notes

The format threw me a bit.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the code's intended behavior and constraints, then systematically identify bugs and performance issues. Propose a fix, analyze its time and space complexity, and discuss whether it's optimal or if trade-offs exist. Always consider edge cases and test your solution.

Pro tip: At Stripe, interviewers value clear communication and the ability to balance correctness with performance. Explicitly state your assumptions and walk through examples to demonstrate your thought process.

1. Understand the Code and Requirements

Ask clarifying questions to confirm the expected behavior, input constraints, and any performance requirements. Restate the problem in your own words to ensure alignment.

2. Identify Issues

Walk through the code line by line, looking for bugs (e.g., off-by-one errors, incorrect logic) and inefficiencies (e.g., unnecessary loops, poor data structures). Use test cases to illustrate problems.

3. Propose a Fix

Describe your solution clearly, explaining how it addresses the identified issues. If multiple approaches exist, briefly compare them and justify your choice.

4. Analyze Optimality

Evaluate the time and space complexity of your fix. Discuss whether it's optimal given the constraints, and if not, what trade-offs are involved (e.g., readability vs. performance).

5. Test and Validate

Walk through edge cases and typical inputs to verify correctness. Mention any additional testing or monitoring you would do in a real-world scenario.

Key Points to Mention

  • Time and space complexity analysis (Big O notation)
  • Edge cases and input validation
  • Trade-offs between different solutions (e.g., readability, maintainability, performance)
  • Use of appropriate data structures and algorithms
  • Potential for parallelization or caching if applicable
  • Real-world considerations like error handling and scalability

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