The Art of Effective Code Reviews
Jonathan Hult
Purpose: Beyond Bug Catching
What is the purpose of a code review? Many teams struggle to define this clearly, leading to ineffective review processes.
Code reviews are not there to catch bugs. For that, we have our automated tests. If the code passed all stages of the deployment pipeline and has been thoroughly tested, the code is releasable. In our case, the purpose of the code review was to convey knowledge, a learning tool and increase code quality.
The Hidden Dangers of Poorly Executed Reviews
It is common sense that releasing code without any review at all is prone to danger. But, is there a danger in a code review itself?
Many times, the way teams execute code reviews adds little or no value other than slowing down delivery. Or even worse, it introduces dysfunctions in the team. Stories of one person solely deciding what comes in[to] the codebase and what not because they are so-called senior, are not uncommon.
Ineffective reviews can create bottlenecks, damage team morale, and establish unhealthy power dynamics. When reviews become gatekeeping exercises rather than collaborative discussions, they undermine their intended purpose and can lead to resentment and reduced productivity.
Creating an Inclusive Review Culture
Who should review who? This question often reveals underlying power dynamics in development teams. Establishing a democratic review process where everyone participates regardless of seniority creates a culture of mutual respect and continuous learning.
There was no hierarchy of who reviews who. Seniors review from seniors and juniors. Juniors review from seniors and juniors. It avoided creating any bottlenecks.
This approach distributes knowledge more evenly across the team and prevents the formation of single points of failure. Junior developers gain confidence and insight by reviewing senior code, while seniors benefit from fresh perspectives.
Clear Expectations for Review Outcomes
What is the expected outcome of a code review? Without clear expectations, reviews can become unfocused and inefficient.
A code review should have one of four outcomes:
1. LGTM [looks good to me]
2. Approved; left some suggestions for your consideration
3. Specific changes requested
4. This whole approach needs to be re-evaluated, let's talk
When providing feedback, Conventional Comments is a great tool to use during Outcomes #2 and #3. This structured format, prefixing the comment with a label like suggestion, nitpick, issue, or question, transforms vague feedback into actionable insights. By clearly signaling intent (and tone), reviewers avoid the common pitfall of ambiguous comments that leave authors wondering, “Is this a blocking concern or just a thought?”
Pair Programming serves as a preventative measure. While it may help reduce instances of Outcome #3 (specific change requests), it excels at preventing Outcome #4 scenarios altogether. Rather than discovering fundamental issues during review, real-time collaboration catches misalignment early, when course correction requires minimal effort. The continuous knowledge exchange during pairing often eliminates the need for extensive post-implementation reviews.
When faced with Outcome #4, recognize it as a clear signal: “stop typing and have a conversation”. Text-based discussions quickly reach diminishing returns when addressing architectural concerns or approach problems. A brief face-to-face conversation can resolve in minutes what might otherwise spiral into days of comment threads and mounting frustration.
Just take five minutes and go talk to them or set up a call if they are working at another location. It almost always works better. For posterity, always note what was discussed/agreed offline back to the PR.
Having clearly defined outcomes helps set expectations and streamlines the review process. When reviewers and authors understand the possible results, they can communicate more effectively and resolve issues more efficiently. Remember that the most productive discussions often happen face-to-face rather than through comments on a pull request.
Best Practices for Effective Reviews
To maximize the value of code reviews:
Focus on knowledge sharing rather than just finding issues
Be timely - quick feedback cycles maintain momentum
Use a consistent approach with clear standards and expectations
Separate style from substance - automate style checks where possible
Maintain a positive tone that encourages collaboration
Know when to talk instead of continuing a comment thread
More reading
Be sure to check out these resources:
Google’s code review processes and policies
Simon Tatham’s code review antipatterns
Max Chernyak’s mindful code reviews
Philipp Hauer's code review guidelines for humans
Dr. Michaela Greiler’s
code review challenges that slow down your productivity
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