Start by clarifying the diff's context and intent, then systematically review from high-level design to low-level details, categorizing comments by severity and type. Emphasize a collaborative tone, focusing on the 'why' behind suggestions and acknowledging trade-offs.
Pro tip: Use a severity scale like [blocker], [suggestion], [nit], and [question] to make your feedback actionable and prioritize what truly matters. Always frame comments as questions or suggestions to foster a learning culture.
Ask about the purpose of the change, the problem it solves, and any constraints. This ensures your review is aligned with the goal and avoids unnecessary comments.
Evaluate if the approach fits the system architecture, scalability, and maintainability. Look for potential trade-offs and suggest alternatives if needed.
Check for bugs, edge cases, error handling, and logical errors. Ensure the code does what it's intended to do under various conditions.
Review naming, comments, formatting, and adherence to style guides. Focus on clarity and consistency, but avoid nitpicking if it's not critical.
Verify that tests cover new functionality and edge cases, and that documentation is updated. Suggest improvements if coverage is lacking.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
I fumbled this by being too vague on the blocker.
Start by briefly defining what each comment type means in a code review context, then write out realistic examples for each as if you were typing them on a pull request. Ensure the examples clearly convey the severity and intent behind each comment type, and explain why you chose the wording.
Pro tip: Use a respectful and constructive tone even for blockers, and make suggestions actionable by including code snippets or specific alternatives. This shows you understand collaboration and code quality.
Briefly explain what a blocker, suggestion, and nit mean in a code review, emphasizing their different levels of severity and required action.
Craft a comment that clearly states a critical issue that must be fixed before merging, explaining the potential consequences and suggesting a fix if possible.
Write a comment that proposes an improvement or alternative approach, framed as a non-blocking recommendation that could enhance the code.
Compose a minor, optional comment about style, formatting, or trivial preferences, explicitly labeling it as a nit to signal low priority.
Briefly justify your wording choices, highlighting how each comment aligns with its intended severity and fosters a positive review culture.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Make your assumptions explicit and phrase uncertainty as questions rather than blockers.
Emphasize a systematic, risk-based approach: first understand the change in isolation by reading the diff and commit message, then infer intent and assess impact using code context and tests. Highlight proactive communication and documentation of assumptions, and show how you balance thoroughness with pragmatism when information is missing.
Pro tip: Focus on what the code does rather than what you think it should do, and use the diff's structure and tests as your primary sources of truth. Document your assumptions and open questions in the review comments so the author can address them asynchronously.
Read the diff carefully, including commit messages and any comments, to grasp what is being changed and why. Identify the scope and potential impact of the change.
Use naming conventions, code patterns, and existing tests to deduce the purpose of the change and how it fits into the surrounding code. Look for clues in the code itself about expected behavior.
Evaluate the change for correctness, edge cases, performance, security, and maintainability. Consider what could go wrong and whether the change aligns with best practices.
Provide constructive feedback, asking clarifying questions where needed and suggesting improvements. Clearly state any assumptions you made due to missing context.
Share your review with the author, highlighting areas of uncertainty and requesting additional information if necessary. Offer to discuss further to resolve ambiguities.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
I said I'd ask them to show me where in the call chain that invariant is enforced.
Acknowledge the author's perspective and seek to understand their reasoning, then collaboratively assess the risk and impact of the edge case. Propose a low-cost mitigation or a time-boxed investigation to validate assumptions, ensuring alignment on quality and delivery.
Pro tip: Frame the discussion around user impact and cost of failure, not who is right. Offer to add a quick test or monitor to catch the edge case in production, turning a potential conflict into a shared learning opportunity.
Show respect for the author's experience and ask clarifying questions to understand why they believe the edge case can't happen.
Evaluate the potential consequences if the edge case does occur, considering user impact, data integrity, and system stability.
Suggest a quick test, monitoring, or a simple guard clause to either prove the edge case is impossible or handle it gracefully.
Agree on a decision that balances quality and delivery, such as time-boxing an investigation or adding a follow-up task.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Acknowledge the design issue but separate it from the current PR's scope. Propose a follow-up ticket or design discussion, and offer to help prioritize it based on impact. This shows you care about code quality without blocking the team's progress.
Pro tip: Frame the issue as a question or observation, not a demand, and tie it to business impact (e.g., scalability, maintainability) to get buy-in without derailing the review.
Confirm that you see the deeper design problem and explain why it matters, but clarify that it's pre-existing and not introduced by this diff.
Evaluate how critical the issue is: does it block the current feature, pose a security risk, or cause performance degradation? If not urgent, it can be deferred.
Suggest creating a separate issue or design doc to address the problem, and offer to collaborate on it after the PR is merged.
Define clear boundaries for the follow-up work, such as a spike, RFC, or refactor task, and estimate effort to help with prioritization.
Discuss with the author and team to ensure everyone agrees on the plan, and document the decision in the PR comments or issue tracker.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
For a junior, you're more explanatory and you assume less shared context.
Acknowledge that review approach should adapt to the engineer's experience and the change's risk profile. Contrast a junior's first PR (focus on learning, mentorship, and correctness) with a staff engineer's critical change (focus on system-wide impact, edge cases, and operational readiness). Emphasize that the core goal remains the same: ensure quality and growth while managing risk.
Pro tip: Frame your answer around risk and growth: junior PRs are about building skills and preventing bad habits, while staff changes are about protecting production and leveraging their expertise. Show you can calibrate feedback to the person and context.
Start by stating that you'd first consider the engineer's experience level and the criticality of the change. This sets the stage for a tailored review.
Focus on mentorship: provide detailed, constructive feedback on code style, testing, and design. Ask questions to guide learning and ensure they understand the 'why' behind changes.
Focus on high-level concerns: system architecture, failure modes, performance, security, and rollback plans. Assume competence and engage in peer-level discussion on trade-offs.
Highlight that both reviews require thoroughness, respect, and alignment with team standards. The difference lies in depth, tone, and the specific aspects you emphasize.
Mention that you'd adjust your approach based on the PR's evolution and feedback, ensuring the review process remains effective and collaborative.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
I said it depends on the team's bar and whether this is a hot path or public API.
Acknowledge that 'obviously correct' is a judgment call and that tests are a form of documentation and risk mitigation. Explain that you would not block outright but would engage in a conversation about risk, context, and alternatives, and describe how you draw the line based on impact, reversibility, and team norms.
Pro tip: Frame the decision as a risk trade-off rather than a binary rule; show that you can be pragmatic while upholding quality standards. Mention that you'd offer to help write the tests or suggest a follow-up ticket if the change is urgent.
Ask about the change's scope, criticality, and whether it's a hotfix or a regular feature. Understand the team's testing culture and existing coverage.
Evaluate the potential impact if the change is wrong, how easily it can be reverted, and whether it touches critical paths. Consider the cost of not having tests versus the cost of delaying.
Suggest alternatives like adding a minimal test, pairing to write tests quickly, or merging with a follow-up ticket if the change is urgent. Avoid an outright block unless the risk is high.
State clear criteria for when you would block: e.g., changes to core logic, security, or data integrity without tests. For low-risk changes, allow flexibility.
Emphasize that the line should be a team agreement, not a personal preference. Suggest discussing and documenting testing expectations to avoid future conflicts.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.