Peer Review Best Practices

Code review is one of the most valuable activities a development team can engage in. When done well, it catches bugs before they reach production, shares knowledge across the team, maintains coding standards, and elevates the skills of every participant. When done poorly, it becomes a bottleneck that breeds resentment and slows delivery. The difference between effective and ineffective code review comes down to the practices and culture your team adopts.

This lesson covers the principles that make peer code review a positive, productive experience for both authors and reviewers. Whether you are reviewing code for the first time or have been doing it for years, these practices will help you provide more useful feedback, maintain a healthy team dynamic, and consistently improve the quality of your codebase.

Why Code Review Matters

Before diving into techniques, it is worth understanding why code review is so important in the first place. The benefits extend far beyond catching bugs:

• Knowledge sharing: Code review is the most effective way to spread knowledge across a team. When you review someone's code, you learn about parts of the codebase you might not work in directly. When someone reviews your code, they bring perspectives and experience that improve the solution. Over time, this cross-pollination means no single person is the only one who understands any given part of the system.
• Bug detection: A second pair of eyes catches issues that the original author overlooked. This is not a reflection of the author's skill — it is a well-documented cognitive phenomenon. We all have blind spots in our own work, and code review systematically compensates for them. Studies have shown that code review catches 60-90% of defects when done consistently.
• Maintaining standards: Without code review, coding standards drift over time. Different developers make different choices, and the codebase becomes inconsistent. Review provides a natural enforcement point where the team's agreed-upon standards are upheld consistently.
• Collective ownership: When multiple people review and understand the code, the team develops collective ownership of the codebase. This reduces risk when team members leave or change roles, and it makes it easier for anyone to fix bugs or add features in any part of the system.
• Design improvement: Reviewers often suggest simpler, more elegant, or more maintainable approaches that the author did not consider. These suggestions compound over time, leading to a codebase that is progressively easier to work with.

How to Be a Good Reviewer

Being an effective reviewer is a skill that takes practice. Here are the principles that guide good review behavior:

Focus on Logic and Architecture, Not Just Style

The most valuable review comments address the substance of the code: Does the logic handle all edge cases? Is the error handling robust? Is the chosen approach appropriate for the problem? Will this design scale as requirements evolve? These are the questions that catch real bugs and prevent future maintenance headaches.

Style issues — formatting, naming preferences, bracket placement — are better handled by automated tools like linters and formatters. If your team has not set up automated style enforcement, do so before spending human review time on whitespace and semicolons. Reserve human review for the things that require human judgment.

Be Constructive, Not Critical

The language you use in review comments has an enormous impact on how they are received. Remember that there is a person on the other end of every review, and that person invested time and effort in the code you are reviewing. Your goal is to help improve the code, not to prove that you are smarter than the author.

Instead of saying "This is wrong," explain why the current approach might cause problems and suggest an alternative. Instead of "You should have used a map here," try "A map might work well here because it would avoid the repeated iteration — what do you think?" Framing suggestions as questions or using collaborative language ("we" instead of "you") makes feedback easier to accept and act on.

Ask Questions Rather Than Making Demands

When you encounter code that confuses you, ask a question rather than assuming it is wrong. The author may have a good reason for their approach that is not immediately obvious from the diff. Questions like "What happens if this value is null?" or "Could this race with the background thread?" are more productive than assertions like "This will crash" because they invite dialogue and often uncover nuances that improve the final solution.

Asking questions also helps junior developers learn to think through edge cases on their own, which is more valuable than simply telling them what to fix.

Suggest Alternatives

When you identify an issue, do not just point it out — suggest a concrete alternative when possible. A comment that says "This could be more efficient" is much less helpful than one that says "Using a Set instead of an Array for this lookup would reduce the time complexity from O(n) to O(1), since we are checking membership frequently." Specific suggestions are easier to act on and help the author learn new patterns.

Review in Small Batches

Do not let pull requests sit in the review queue for days. Research consistently shows that review quality declines significantly after the first 60-90 minutes of review time, and that reviewers are less effective when reviewing more than 400 lines of code at once. If a PR is too large to review in one sitting, that is a signal that it should have been broken into smaller PRs.

Set aside dedicated time each day for code review. Many teams find that reviewing first thing in the morning or immediately after lunch works well. The key is to make review a regular habit rather than something you do when you "find time" — because you will never find time if you do not make it.

Aim to respond to review requests within a few hours, not a few days. Fast feedback keeps the author in context, reduces work-in-progress, and prevents merge conflicts from accumulating. If you cannot review a PR promptly, communicate that so the author can find another reviewer.

What to Look For

A thorough review examines the code across multiple dimensions. Here is what to focus on, roughly in order of importance:

• Correctness: Does the code actually do what it claims to do? Does it handle edge cases, boundary conditions, and error paths? Are there off-by-one errors, null reference risks, or incorrect assumptions about input data?
• Security: Does the code handle user input safely? Are there SQL injection risks, XSS vulnerabilities, or authentication bypasses? Are secrets properly managed? Does the code follow the principle of least privilege?
• Accessibility: If the change touches user interface code, does it maintain or improve accessibility? Are ARIA attributes correct? Does keyboard navigation work? Are color contrast ratios sufficient? Is semantic HTML used appropriately?
• Performance: Are there obvious performance issues like N+1 queries, unnecessary re-renders, blocking I/O on the main thread, or missing pagination for large datasets? Is caching used where appropriate?
• Readability: Can a developer unfamiliar with this code understand what it does and why? Are variable and function names descriptive? Are complex algorithms commented? Is the code organized logically?
• Test coverage: Does the PR include tests for new functionality? Do the tests verify the right behavior? Are edge cases tested? Are the tests themselves readable and maintainable?

Conventional Comments

One of the most effective practices for improving review communication is the "Conventional Comments" system. This approach adds a prefix to each review comment that communicates its intent and importance. It eliminates ambiguity about whether a comment is a required change or a minor observation, which is one of the most common sources of friction in code review.

The standard prefixes are:

• nitpick: A minor, non-blocking style or preference suggestion. These are things the reviewer would do differently but that do not need to be changed. Examples: "nitpick: I'd name this variable userCount instead of cnt" or "nitpick: could move this constant to the top of the file."
• suggestion: A non-blocking recommendation for improvement. The author should consider it but does not need to implement it. Example: "suggestion: extracting this into a helper function would make it reusable in the admin panel too."
• issue: A problem that must be addressed before the PR can be merged. This is a blocking comment. Example: "issue: this query is vulnerable to SQL injection because user input is concatenated directly into the query string."
• question: A genuine question about the code, not a veiled criticism. Example: "question: does this need to handle the case where the user has been soft-deleted?"
• thought: An observation or idea that does not require action. Example: "thought: we might want to revisit this pattern when we migrate to the new auth system next quarter."
• praise: Positive feedback for something done well. Example: "praise: great use of the builder pattern here — this is really clean and extensible."

Using these prefixes transforms code review from a guessing game into clear communication. Authors immediately know which comments are blocking and which are suggestions, so they can prioritize their time effectively. Reviewers feel more comfortable leaving minor observations because they know the "nitpick:" prefix communicates that the comment is not a demand.

Code Review as Mentorship

Code review is one of the most powerful mentorship tools available to a development team. Every review is an opportunity for both the author and the reviewer to learn something new.

For senior developers reviewing junior developers' code, review is a chance to teach design patterns, share institutional knowledge, and help new team members understand the "why" behind coding conventions. Instead of just pointing out what to change, explain the reasoning behind your suggestion. A comment like "We use the repository pattern here because it makes our data access layer testable and allows us to swap databases without changing business logic" teaches a principle, not just a rule.

For junior developers reviewing senior developers' code, review is a chance to learn by studying well-written code and asking questions about unfamiliar patterns. Do not hesitate to ask "why" when something is not clear — your question might reveal an assumption that needs to be documented, or it might lead to a simpler approach that benefits everyone.

For peers at similar experience levels, review is a chance to exchange techniques and approaches. You might discover that your colleague has a more elegant solution to a problem you have been struggling with, or that your fresh perspective catches an issue that familiarity made invisible.

The key to making code review work as mentorship is psychological safety. Team members must feel safe asking questions, making mistakes, and receiving feedback without fear of judgment or embarrassment. This safety starts with leadership and is reinforced by every interaction in every review. When a team has this safety, code review becomes something people look forward to rather than dread.