Common Code Review Mistakes Developers Make (And How to Fix Them)

Code reviews are a cornerstone of modern software development. They serve as checkpoints where developers can detect code mistakes, identify areas of improvement, and collectively maintain a robust codebase. However, while the benefits of code reviews are widely acknowledged, many teams still encounter significant code review challenges that can lead to frustration, stalled delivery, or poor-quality software.

In this article, we'll walk through the most frequent code review mistakes developers make, delve into practical solutions, and show how to leverage both manual code review and automated code review methods. By understanding these pitfalls and how to sidestep them, your team will minimize common coding mistakes, reduce code review conflicts, and optimize overall workflow efficiency. Let's explore why code reviews are crucial, identify key pitfalls to avoid, and highlight strategies for more effective collaborations.

Why Code Reviews Matter

Before dissecting the typical code review mistakes, let's emphasize why code reviews matter so much in any development life cycle. Here are a few critical benefits of code reviews:

Ensures Code Quality
By catching coding mistakes during peer review, you can substantially reduce the risk of bugs in production. This early feedback loop helps maintain a healthy, consistent codebase.
Promotes Team Alignment
When everyone routinely reviews each other's code, knowledge gets shared, and developers gain insights into different parts of the system. This fosters team coherence and fewer code review conflicts.
Encourages Best Practices
Code reviews serve as a platform to reinforce code reviews best practices. Senior developers can guide junior developers on common coding mistakes, security considerations, and performance optimizations.
Reduces Overall Costs
The costs of debugging code mistakes skyrocket once software is in production. Systematic code reviews help identify issues early and minimize rework down the road.
Builds a Stronger Feedback Culture
Constructive reviews build trust and an environment where everyone feels comfortable sharing ideas, discussing code review challenges, and focusing on continuous improvement.

Ultimately, an organized code review (read more) process—whether it's done via manual code review or enhanced with automated code review—pays huge dividends, especially in complex projects. By ensuring the right checks, you'll catch coding mistakes, mitigate future issues, and enhance team collaboration.

Common Code Review Mistakes Developers Make

Despite the benefits of code reviews, it's all too easy to slip into inefficient or unproductive practices. Below are the core code review mistakes that commonly derail teams, each followed by actionable fixes.

Overlooking Code Standards

Mistake: Failing to adhere to coding guidelines and standards.

Among the most pervasive code review mistakes is ignoring established coding conventions. Each development team typically has a style guide—either an internal document or a popular industry standard. However, when reviewers don't enforce these guidelines consistently, coding mistakes that violate style or format can slip through, creating fragmentation and even code review conflicts over time.

Solution: Establish clear coding standards and use linters/formatters to automate checks.

Document Your Guidelines
Create or adopt a widely recognized style guide (e.g., Airbnb for JavaScript) to ensure everyone is on the same page.
Automate with Linters
Incorporate linting tools, like ESLint or RuboCop, directly into your CI pipeline for immediate feedback on style-based code mistakes.
Reference Standards in PR Templates
Remind developers about your coding standards by linking them within pull request templates.

For deeper insights into how to write cleaner code, see our dedicated post on how to write code.

Reviewing Only Newly Added Code

Mistake: Focusing solely on new or changed code can lead to a fragmented understanding of the codebase.

It's tempting to zero in exclusively on fresh diffs. While this approach might seem time-efficient, it risks overlooking how new changes integrate with existing logic or architecture. This siloed review can lead to overlooked code mistakes that surface much later.

Solution: Review the entire codebase context to ensure that new changes integrate seamlessly with existing code.

Expand the View
Many Git platforms let you expand surrounding lines in a diff. Use this to evaluate the context of the changes.
Cross-File Checks
If a pull request touches multiple areas, glance through all relevant files to catch cross-cutting coding mistakes.
Encourage Discussion
If something seems off or ambiguous, ask questions in the code review comments to avoid larger code review conflicts later.

Focusing Only on Syntax, Not Logic

Mistake: Concentrating on minor syntax errors while missing logical flaws.

Syntax issues are easy to spot and can sometimes overshadow deeper design or logical errors—especially when automated linters flag them immediately. Overemphasizing small style points may cause reviewers to gloss over critical code mistakes in how data flows or how functions interact.

Solution: Encourage reviewers to prioritize functionality and logic over superficial issues.

Separate Style Checks
Use automated code review tools to handle formatting. This frees up human reviewers to focus on logic.
Apply a Review Checklist
Incorporate questions about business logic, performance, and security, not just style.
Educate the Team
Regularly remind everyone that code review challenges often lie in higher-level logic, which no linter can fully capture.

Ignoring Context or Requirements

Mistake: Reviewing code without understanding the problem it solves.

Reviewers sometimes dive into code without referencing the user story, design docs, or specs. As a result, critical code mistakes might be missed because the reviewer doesn't fully grasp the intended functionality.

Solution: Provide adequate documentation or context in pull requests.

Mandatory Descriptions
Pull requests should include a clear problem statement, links to tickets, and expected outcomes.
Tag Relevant Issues
If you use a project management tool like Jira or Trello, provide direct links so reviewers can see the broader context.
Ask for Clarification
Don't hesitate to request additional details if requirements or objectives aren't crystal clear.

Having the right context at the right time also prevents context switching in your development process, which can otherwise slow teams down. Read more about context switching to understand how it affects productivity.

Lack of Constructive Feedback

Mistake: Giving vague or overly critical feedback.

One of the biggest code review mistakes developers make is failing to provide actionable, empathetic feedback. Comments like "This is wrong" or "Rewrite this" without further guidance can create tension, leading to code review conflicts and diminishing the trust that's so vital for effective collaboration.

Solution: Use constructive, specific, and actionable comments.

Focus on the 'Why'
Rather than just pointing out errors, explain the rationale behind suggested changes.
Propose Alternatives
If you see code mistakes in logic or structure, offer alternative approaches or direct references to docs.
Balance Positive and Negative
Commend good solutions or improvements, and then address the issues that need attention.

Cultivating a strong feedback culture often extends beyond code reviews. Daily standups or using the best Slack standup bot can keep everyone aligned and engaged.

Reviewing Too Much Code at Once

Mistake: Large pull requests lead to fatigue and missed issues.

Massive pull requests can overwhelm reviewers, increasing the likelihood of overlooked code mistakes. When PRs contain hundreds or thousands of lines, fatigue sets in, making thorough reviews nearly impossible.

Solution: Break down pull requests into manageable chunks.

Set PR Size Guidelines
Agree on a limit for lines of code or functional scope per PR.
Encourage Incremental Commits
Smaller, well-defined commits are easier to review and revert if needed.
Maintain a Regular Review Cadence
Setting frequent, shorter review sessions prevents backlog buildup.

Skipping Security or Performance Considerations

Mistake: Focusing on functionality while ignoring security and performance implications.

Teams often consider a pull request "good enough" if it works as intended. But ignoring potential security flaws or performance bottlenecks can be one of the most damaging code review mistakes in the long run.

Solution: Include security and performance checks in the review checklist.

Adopt a Security Mindset
Build threat modeling into your manual code review process. Ask how an attacker could misuse the feature.
Profile for Performance
Encourage developers to assess time complexity, memory usage, and potential load issues before finalizing.
Use a Code Review Checklist
A dedicated checklist ensures consistent inspection of crucial areas. Check out our code review checklist for more guidance.

Being Too Lenient or Too Critical

Mistake: Letting mistakes slide or being overly strict, creating friction in the team.

Striking the right balance can be challenging. Being too lax allows common coding mistakes to go unchecked, while an overly strict approach can sap morale and stifle innovation—both scenarios leading to code review conflicts.

Solution: Balance review tone to be collaborative and constructive.

Define 'Blocker' vs. 'Non-Blocker'
Clarify when a comment is a suggestion versus a requirement for merging, so small code mistakes don't hold up progress unnecessarily.
Encourage Teamwide Participation
Multiple reviewers can prevent any single perspective from dominating and creating an imbalance.
Foster Psychological Safety
Create an environment where developers feel safe pointing out potential code mistakes, no matter who wrote the code.

Delayed Reviews

Mistake: Taking too long to review code, delaying progress.

Long review cycles lead to significant context switching, as developers switch tasks while waiting on feedback. This not only blocks merges but can introduce new code mistakes when developers resume partially completed tasks.

Solution: Set clear expectations for review timelines and prioritize code reviews.

Establish Response Windows
For instance, require that reviews begin within 24 hours of a pull request's submission.
Leverage Reminders
Automate Slack or GitHub scheduled reminders so reviews don't slip through the cracks.
Incentivize Prompt Feedback
Recognize and reward teams or individuals who consistently provide timely, quality reviews.

Human, Automated, or Hybrid Code Review?

Choosing between a manual code review process, an automated code review setup, or a hybrid of both involves considering your project's size, complexity, and the team's skill level. Each approach has its benefits and caveats:

1. Manual (Human) Reviews

Manual code review is the traditional route. Humans can spot nuanced code mistakes, architectural flaws, or unclear requirements that machines might miss. Yet, manual reviews can be time-consuming and prone to reviewer fatigue, especially if the team handles numerous pull requests daily.

2. Automated Reviews

Using automated code review solutions like ESLint, SonarQube, or CodeClimate speeds up the detection of syntax errors, style issues, and certain common coding mistakes. These tools shine by providing immediate feedback and ensuring consistency. However, automation alone can't fully grasp business logic or complex architectural considerations.

3. Hybrid Reviews

Many teams find the sweet spot in a hybrid approach: let automated code review handle repetitive checks, while human reviewers focus on logic, design patterns, and potential code review challenges that require deeper analysis. This division of labor maximizes efficiency and minimizes coding mistakes slipping through the cracks.

4. AI-Powered Code Reviews

Emerging AI-driven solutions are taking automation a step further. These tools can sometimes suggest fixes, detect suspicious patterns in large codebases, and learn from past merges to predict potential code mistakes. While AI code review platforms are still evolving, they're worth exploring if you're aiming to enhance your existing code reviews best practices. For an in-depth look at the possibilities, see our piece on AI code review.

Whichever path you choose, understanding types of code review (https://axolo.co/blog/p/types-of-code-reviews-maximizing-your-code-quality) ensures your team can adapt and refine its strategy over time.

Popular Tools and Assets for Code Reviewing

Below are some widely used tools and practices to streamline your code reviews best practices, minimize code mistakes, and address code review challenges head-on:

GitHub Pull Requests and Slack Integration
- GitHub's PR feature is comprehensive, but integrating it with Slack keeps teams aligned. Explore the github slack integration for real-time notifications and smoother collaboration.
GitLab Merge Requests
- Similar to GitHub, GitLab offers strong built-in review workflows. If your team is on GitLab, check our guide on code review in GitLab to make the most of these tools.
Automated Code Review Tools
- Tools like SonarQube, ESLint, and CodeClimate can detect style issues, potential security threats, and common coding mistakes early. Having these run automatically in your CI/CD pipeline ensures faster feedback.
Peer Review Process Enhancements
- Solutions like Axolo centralize the peer review process in Slack, ensuring timely feedback and easier referencing of PRs. Another tip: set up GitHub scheduled reminders to ping reviewers about pending tasks.
Templates and Checklists
- Standardize your code review practices by incorporating templates that prompt reviewers to check everything from syntax to performance. Use our code review checklist for a solid starting point.

Ready to Improve? Start Fixing Code Review Mistakes Today

Improving your code review process to address code review mistakes isn't just about avoiding errors—it's about building a strong, cohesive team culture that values knowledge sharing, efficiency, and quality. Below are some steps to help you get started:

Document Your Process
- Whether you lean on manual code review, automated code review, or a hybrid model, ensure the steps are well-documented. Define when a review is required, who reviews it, and the acceptance criteria.
Prioritize Smaller Pull Requests
- Large PRs create code review challenges, so break changes into logical, smaller segments. This approach yields quicker reviews and helps catch coding mistakes faster.
Utilize Tools and Integrations
- A robust github slack integration or scheduled reminders can keep your team on track and reduce delays. By automating routine checks, you free up more time for deeper human analysis.
Embrace Continuous Learning
- Keep the team updated about emerging best practices or common coding mistakes. Host internal knowledge-sharing sessions or direct teammates to relevant blog posts on how to write code more effectively.
Encourage Healthy Feedback Loops
- Remember, code review mistakes often stem from a lack of clarity or overly negative remarks. Constructive communication and empathy can avert code review conflicts and improve morale.
Implement Timely Review Policies
- Frequent reminders (e.g., GitHub scheduled reminders) maintain momentum and limit context switching. When you prioritize code reviews, you minimize bottlenecks.

By making incremental improvements—like clarifying guidelines, adopting a balanced mix of automation and manual checks, and fostering constructive dialogue—your team will rapidly see the benefits of code reviews. You'll deliver higher-quality code, mitigate common coding mistakes, and prevent the sort of code review conflicts that derail progress.

Final Thoughts

Effective code reviews are about more than just spotting minor errors. They're an opportunity to cultivate a culture of shared responsibility, knowledge transfer, and continuous refinement. By avoiding code review mistakes, balancing thorough manual code review efforts with the speed of automated code review, and keeping your team engaged and supported, you'll build software that's robust, efficient, and aligned with your project goals.

Stay proactive in refining your code review practices. Use checklists, adopt the right tools, promote clarity and empathy in feedback, and tackle code review challenges before they become major roadblocks. Over time, you'll find your team delivering better, more consistent code—and you'll see firsthand the lasting benefits of code reviews on overall product quality.

If you're ready to begin, consider implementing one improvement at a time—like establishing maximum PR sizes or setting up GitHub scheduled reminders. Small steps can spark a significant transformation in your development process. Here's to fewer coding mistakes, fewer code review conflicts, and a more productive, collaborative future!