Stripe SWE Interview: Bug Squash Guide

Estimated read time: 8-10 minutes

Summary: Stripe's Bug Squash interview is one of the clearest Stripe software engineer (SWE) rounds. Expect side-by-side debugging on a real historical bug in an open-source project in your language, with written rubrics guiding the evaluation.

TL;DR + FAQ (read this first)

At-a-glance takeaways

• Bug Squash is about systematic debugging in unfamiliar code, not instant codebase mastery.
• Reproduce the failure before changing code, then use evidence to narrow the path.
• A targeted fix plus regression coverage is stronger than a broad rewrite.
• Senior candidates should discuss related risks and longer-term maintainability after the fix.

Quick FAQ

What should I do first?
Reproduce the bug and describe what would prove the suspected cause.

Can I ask questions?
Yes. Collaborative debugging is part of the signal.

What is the main failure mode?
Random edits without a clear hypothesis, test, or validation step.

At a glance

• Stage: Onsite.
• Round: Bug Squash.
• Typical duration: often 45-60 minutes; confirm with your recruiter.
• Likely interviewer: engineer working side by side with you.
• Format note: side-by-side debugging is the defining setup for this round.

What happens in this round

You and the interviewer debug unfamiliar code together, using a real historical bug in an open-source project in your language. The goal is not to instantly know the codebase. The goal is to reproduce the issue, form hypotheses, inspect the relevant path, make a targeted fix, validate it, and communicate clearly.

Assume the interviewer is looking for repeatable debugging behavior: systematic investigation, collaboration, tests, code reading, and a fix that matches the observed failure.

Level-specific expectations

Intern and new grad candidates should show calm code reading, hypothesis-driven debugging, and willingness to ask clarifying questions.

Junior and mid-level candidates should reproduce, isolate, fix, and validate without thrashing.

Senior and staff candidates should add broader implications: regression coverage, maintainability, related failure modes, and reliability impact.

Candidate-facing questions to prepare

• Given an unfamiliar codebase and a failing test, reproduce the failure and identify the smallest suspicious path.
• Use a stack trace to form a debugging hypothesis, then prove or disprove it with code inspection.
• Patch a historical bug without rewriting unrelated parts of the codebase.
• Add a regression test that would have caught the bug before the fix.
• Explain your debugging steps as you move from symptom to root cause.
• Trace an API failure through parsing, validation, state updates, and error handling.
• For senior candidates: explain what related failures you would audit after landing the fix.

Strong signals

• Reproducing the bug before changing code.
• Using hypotheses, logs, tests, stack traces, and code reading deliberately.
• Making the smallest reasonable fix.
• Adding or describing regression coverage.
• Collaborating calmly in unfamiliar code.

Common failure modes

Random edits. Debugging should be evidence-driven.

Skipping reproduction. If you cannot reproduce the failure, you cannot prove the fix.

Rewriting instead of debugging. The round is about code navigation and targeted repair.

How to prepare

• Practice debugging small open-source issues or unfamiliar repositories in your strongest language.
• Review stack traces, tests, logging, breakpoints, and reading code by call path.
• Get comfortable saying what you are checking and why.
• Prefer small, targeted fixes with validation.
• For senior roles, discuss related risk and longer-term maintainability after the fix.