How often do developers create pull requests (PRs) just because the process requires it, without thinking about their actual value?
And how frequently does your PR sit unreviewed for days because all potential reviewers are busy?
On the other hand, some might want to skip this part of the process:

“I’ve only changed one line of code. Can I push it to master?”

What could go wrong?

• A critical bug in production.
• Sensitive data is exposed.
• The team has no visibility into what changed.
• Developers experience burnout due to inefficient and frustrating review cycles.

Code reviews are essential, but if not structured well, they become a bottleneck instead of a productivity tool.

This article explores common code review challenges and practical solutions to make the process faster, more effective, and enjoyable for everyone.

Goals of the Code Review

Code reviews are not just about catching bugs. Well-structured code review process should:

• Ensure code quality – Reviewers provide valuable insights to improve the code.
• Maintain consistency – Code style, patterns, and best practices remain aligned across the team.
• Enable knowledge sharing – Developers learn from each other through reviews.
• Offer a fresh perspective – The author may miss issues another developer can spot.

However, without a clear structure, these benefits are often lost.

Code Review Problems and Possible Fixes

Reviews are too slow, or “no time for code review”

Example scenario: A developer submits a PR on Monday. By Friday, it’s still waiting for a review.

Can someone review my PR?

Yeah, I’ll get to it soon…[everyone is busy with urgent stuff]

By the time someone finally looks at it, the author has lost context, making it harder to address feedback efficiently.

How to fix it:

• Dedicated time slot for reviews—Some teams implement a “Morning review hour,” where engineers spend the first 30 minutes of their day reviewing PRs before diving into deep work. This helps to avoid delays caused by context-switching.
  
• Use team agreements to align expectations around how quickly PRs should be reviewed; for example – “PRs should be reviewed within 24 hours”
  
• Set up well-defined statuses (e.g., “ready for review,” “needs work,” “blocked,” “ready for merge”) that reflect progress.
  
• Align on the code style so there will be no disputes around the code style preferences.
  
• Dedicated Slack channel for the PRs that need attention; automatic reminders set up for PRs that are waiting too long.
  
• Improve commenting techniques to make the process faster
  • Use prefixes in comments to streamline discussions so the creator knows if it is a blocker or suggestion.
  • Write what exactly you took a look at if not everything was reviewed.
    
• Introduce a code review checklist, which could include the following steps:
  • Is the code well-structured and easy to understand?
  • Are functions and classes small and modular?
  • Are there any potential race conditions or concurrency issues?
  • Does the code introduce unnecessary dependencies?
  • Are API keys, credentials, or sensitive data hardcoded?
    
• Ensure PRs have clear descriptions. The description should outline what changed, why it changed, and any areas of focus for the review. It may also contain any additional information that could help reviewers.
  
  • Title
  • What changed?
  • Why?
  • What to check?
  • How is it tested?
  • Potential risks & mitigations

• Provide clear documentation in the code, which helps to understand the logic behind the changes.
  
• Separate logical parts into different commits in the PRs and make the proper message; this could help the reviewer to navigate through changes.

While speeding up PR reviews is crucial, it’s only part of the solution. Many bottlenecks also come from a lack of automation and PRs that are too large to review efficiently.

Large, complex PRs are intimidating and hard to review effectively

Example scenario: A developer created PR with 1000+ lines of code changed.

The title? – “Refactoring + feature + bug fixes + cleanup + magic”

As a result, no one wanted to review it. When someone finally looks at it, they request dozens of changes, and the cycle repeats.

How to fix it:

• Limit PR size—Teams could use a “Max x lines per PR” rule (e.g., 200 – 400 lines). Research suggests that the optimal code review rate is between 200 and 400 lines per hour. Productivity and defect detection ability significantly drop after an hour of continuous review.

source: smartbear.com

• Break changes into multiple PRs:
  PR 1 – Refactoring.
  PR 2 – Adding the feature.
  PR 3 – Fixing UI issues.
  
• For large changes, schedule a “Team Code Review” (TCR) meeting where the author explains the key changes before submission. This will make it easier to actually review the code.

No volunteers to review the code

Example scenario: In an engineering team, only the tech lead consistently reviewed PRs.

The rest of the team hesitated, thinking: “He knows the codebase best, so I’ll let him handle it.”

Over time, this became a bottleneck—the lead was overwhelmed, reviews slowed, and the team was not aligned on the code base.

How to fix it:

• Implement review rotations. Every team member will participate in reviews. PRs will be distributed better, preventing burnout. Junior developers will improve their skills by taking ownership. The tech leaders will be freed up for other strategic tasks instead of only reviewing.
  
• Assign a “review duty” each sprint – One engineer is responsible for making sure reviews happen.
  
• Encourage team engagement – Tracking who is the most active commenter on PRs, which PRs took longer than others can highlight imbalances.
  
• Limit code review sessions to a maximum of 60 minutes per day. As mentioned earlier, productivity and defect detection ability drop significantly after an hour of continuous review.
  
• Provide the team with information about the goals of the Code Review practice and ensure alignment based on the team’s agreement on the topic.
  
• Establish a positive code review culture where feedback is constructive and good practices are recognized (be objective, not personal; explain why; offer alternatives; encourage collaboration)
  
  🚫 “You forgot to handle edge cases.”
  ✅ “I see the main logic is solid. Just wondering, how does this handle cases where the input is empty? Maybe we could add a test for that?”

Lack of automation

Example: Review comments are filled with:

Fix indentation.
This function name should be camelCase.
Did you write tests for this?

Instead of focusing on logic and architecture, reviewers spend time pointing out issues that could be checked automatically.

How to fix it:

• Run automated tests in CI/CD—PRs should not be allowed to merge if tests fail. Measuring test coverage could also be done; however, it serves as information rather than a metric that guarantees the functionality is well-tested.
  
• Automate formatting – Use tools like Prettier and ESLint to apply consistent styling automatically.
  
• Use static analysis tools that can catch security vulnerabilities, and code smells (e. g. SonarQube).
  
• Tracking PR review patterns and efficiency metrics could help identify patterns that could be improved, such as when only one person reviews PRs or when some PRs are reviewed longer than others, which PRs are getting stuck.

When Code Reviews May Not Be Necessary

Example scenario: A high-traffic platform experiences a critical production outage. The team has an urgent fix ready, but if they wait for a formal review, millions of dollars could be lost in just a few hours.

Instead of waiting, they applied an emergency fix immediately and agreed to do the review afterward, ensuring the long-term stability of the codebase.

Not every change needs a formal review, considering that automated checks were done. Teams can define exceptions for situations like:

• Emergency Fixes: Allow expedited processes for critical bugs, however completely skipping reviews for even emergency fixes can be risky. One approach is ‘post-mortem reviews’ – after deployment, the fix is reviewed retrospectively.
  
• Pair Programming: Real-time collaboration to replace code reviews could be applicable in some cases, rotate pairs regularly to spread knowledge across the team.
  
• Isolated Changes: You could have in your team agreement that reviews are not necessary for small, well-contained updates if appropriate automated checks are in place.

Building an Efficient Code Review Process

By solving the problems mentioned above, teams can transform PRs from a bottleneck into a productive workflow.

The code review process should work for the team, not against it.

Code reviews aren’t just about catching bugs – they’re an opportunity to foster collaboration, maintain code quality, and strengthen team trust.

To make them truly effective:

• Set clear expectations – Define review timelines and responsibilities.
• Make PRs easy to review – Keep them small and well-documented.
• Automate what you can – Use automation tools to eliminate repetitive tasks.
• Encourage collaboration – Reviews should be a learning opportunity, not just a process step.

Before submitting your next PR, ask yourself:

“How can I make this review easier for my teammates? How can we improve our code review practices today?”

By taking small, deliberate steps to streamline reviews, advocating for process improvement, and starting to make small improvements, you’ll create a process that supports your team and your product—not one that holds them back.