Code reviews are the cornerstone of high-quality software development. By systematically examining code before it’s merged into the main codebase, you can catch bugs, improve code quality, and streamline workflows. 

This growing impact is reflected in market trends; analysts project the global code review tools market to hit USD 2.5 billion by 2030, expanding at a CAGR of over 25%. 

However, the impact of code reviews goes beyond cleaner code. A well-structured process strengthens collaboration, promotes knowledge sharing, and ultimately drives better project outcomes.

This blog explores best practices for conducting effective code reviews, emphasizing time-saving strategies, improved communication, and enhanced project outcomes.

Key Takeaways:

• A clear and structured code review process is essential for maintaining high-quality software and improving team collaboration.

• Small, incremental pull requests are more effective for efficient code reviews and prevent reviewer fatigue.

• Integrating automation and CI tools into the review process helps streamline workflows. This helps in reducing the time spent on manual tasks and speeding up feedback loops.

• A positive feedback culture encourages continuous learning and improves overall code quality.

• Encouraging self-reviews before peer reviews helps you catch common issues and take ownership of their code.

What is Code Review?

Code review is the practice of systematically reviewing code before it’s integrated into the main codebase. The primary goal is to identify potential bugs, enhance code quality, ensure adherence to best practices, and facilitate effective collaboration. 

But, beyond these basics, the primary advantage of code reviews is how they improve productivity and streamline workflows, facilitate learning, and maintain long-term code health.

Overall, with a system in place, you can ensure that every line of code meets the standard and is ready for deployment.

Why Code Reviews Matter?

Code reviews enhance code quality and promote knowledge sharing among developers. It accelerates onboarding, improves your productivity, and saves time by identifying issues early, preventing bugs, and streamlining workflows. Let’s look at why code reviews are important:

1. Improved Code Quality

Effective code reviews are instrumental in maintaining high-quality software. By regularly reviewing code, you can identify bugs, spot opportunities for refactoring, and reduce technical debt. Instead of patching issues after deployment, you and your team can prevent them from occurring in the first place.

2. Knowledge Sharing & Mentorship

A code review is an opportunity for junior developers to learn from senior team members. Senior engineers can mentor others by sharing best practices, offering explanations, and guiding less-experienced coders through complex problems. It’s a powerful way to grow team talent.

3. Improved Estimates & Faster Onboarding

When code is reviewed regularly, you gain valuable insights into the project’s progress and potential roadblocks. Reviews also serve as a training ground for new developers, helping them become familiar with the project’s codebase faster and improving their estimation skills.

4. Increased Productivity & Time Savings

It might seem like reviews take time, but in reality, they save time in the long run. Effective reviews catch potential issues early, reducing the need for later bug fixes or patches. They streamline workflows by identifying performance bottlenecks and promoting the use of optimized, clean code.

5. Time-Optimized Practices

Well-managed code reviews can significantly reduce the time you spend firefighting later. By spotting and resolving bugs earlier in the process, you can reduce the chances of encountering larger issues in later stages of development.

Now that we've established the importance of code reviews, let’s delve into some of the best practices for code reviews.

Best Practices for Code Reviews (Core Principles for Effective Reviews)

Code reviews become significantly more effective when structured correctly. Here are 12 best practices that will help you maximize the value of your code review process.

1. Establish a Clear Review Process

Establishing a clear review process means setting expectations for what needs to be reviewed and why. This includes focusing on specific areas like bug detection, performance optimization, and adherence to coding standards. 

How to Implement:

• Define goals for each review (bug fixes, performance checks, adherence to best practices).

• Create a workflow template and document the process clearly.

• Set guidelines for the size of code changes and expected turnaround time for reviews.

• Assign responsibilities (e.g., who reviews what areas: security, performance, functionality).

2. Focus on Key Aspects of the Code

Code reviews should prioritize readability, maintainability, performance, and security. Ensuring that code is clear and easy to maintain improves long-term project scalability and prevents technical debt. Moreover, security must always be a top concern to prevent vulnerabilities and ensure data integrity.

How to Implement:

• Set specific goals for readability, such as clear naming conventions and simple code structures.

• Create performance benchmarks for what constitutes efficient code.

• Regularly check for common security vulnerabilities and integrate security scans into the review process.

• Encourage the use of design patterns that promote maintainability.

3. Review Small Code Segments

Large code reviews can be overwhelming and inefficient. By limiting each review to small, manageable code segments (around 400 lines), you can maintain focus, reduce reviewer fatigue, and ensure quality checks are thorough without rushing.

How to Implement:

• Set a maximum limit for pull request (PR) size (e.g., 400 lines of code).

• Break down larger features into smaller, logical PRs to make them easier to review.

• Implement a process where you submit smaller, more frequent changes instead of massive updates.

4. Use Checklists

A checklist helps standardize the review process, ensuring that key aspects like code formatting, efficiency, and security aren’t overlooked. It also promotes consistency, so all code reviews meet the same quality standards.

How to Implement:

• Develop a comprehensive code review checklist covering style, performance, security, and functionality.

• Make the checklist easily accessible to reviewers during each review.

• Continuously update the checklist based on your feedback and evolving project needs.

• Use checklist templates that reviewers can customize as per the task at hand.

5. Collaborate Early

Engaging in code reviews early in the development cycle, rather than waiting until the final stages, helps maintain code quality from the start. It also ensures that you and your team can address any issues while they’re still working on the code.

How to Implement:

• Set up regular checkpoints or review milestones within the development cycle.

• Encourage informal reviews of code in progress rather than waiting for final submissions.

• Use collaboration tools to give feedback while the code is still being written.

6. Keep Pull Requests Small & Incremental

Large PRs can overwhelm reviewers and increase the chance of important details being missed. Small, incremental PRs make the review process smoother and faster by allowing reviewers to focus on one task at a time.

How to Implement:

• Encourage the submission of one logical change per PR.

• Break up large features or bug fixes into smaller tasks, each with its own PR.

• Set clear guidelines on PR size, ensuring each review focuses on specific, actionable parts of the code.

7. Ensure Actionable Feedback

Feedback should be specific, actionable, and focused on improvement. Vague comments or suggestions for vague fixes can leave you confused and unsure of how to proceed. Meanwhile, clear feedback helps drive the quality of the code forward.

How to Implement:

• Be specific about what’s wrong and provide concrete suggestions for how to fix it.

• Avoid general statements like "This code could be better."

• Make sure to prioritize feedback based on the severity of the issue (e.g., critical bugs first).

• Encourage positive reinforcement for well-written code, along with areas for improvement.

8. Use Continuous Integration and Automated Tools

Continuous Integration (CI) tools and automated testing reduce the manual load during the review process. These tools can check for common issues like syntax errors, testing failures, and style violations, allowing reviewers to focus on more complex aspects of the code.

How to Implement:

• Set up automated linting and unit testing in your CI/CD pipeline.

• Integrate tools like static analysis tools, security scanners, and test runners into the review workflow.

• Use automated code reviews for basic checks, leaving human reviewers to focus on architecture and logic.

Also Read: Introducing the Entelligence AI Code Review in Your IDE!

9. Promote a Positive Feedback Culture

Building a culture of constructive feedback is important for successful code reviews. A positive environment encourages you to share knowledge, make improvements, and learn from your mistakes without feeling discouraged.

How to Implement:

• Set guidelines for giving and receiving feedback in a constructive, respectful manner.

• Promote feedback that is solution-oriented and encourages learning.

• Recognize and celebrate well-written code in reviews to motivate others.

• Encourage open dialogue where you feel comfortable asking questions and offering suggestions.

10. Encourage Self-Reviews

Before submitting code for peer review, you should review your own work. This builds accountability and often catches issues that might have been overlooked during development, reducing the workload on reviewers.

How to Implement:

• Require you and your team to perform a self-review checklist before submitting code.

• Implement peer review reminders where you must ensure that you check common issues (e.g., formatting, logic, edge cases).

• Allow yourself and your teammates to review their code in stages, checking for functionality and quality before submitting to peers.

11. Use Explicit Review Requests

Explicitly requesting a review from the right person ensures that the review process is both focused and efficient. It helps avoid delays and ensures that the reviewer is knowledgeable about the specific areas that need attention.

How to Implement:

• Tag appropriate team members in pull requests based on their expertise (e.g., security, database, frontend).

• Set expectations about who reviews what to streamline the review process.

• Use project management or collaboration tools (e.g., Jira, Slack) to ensure the correct reviewers are notified.

12. Documentation & PR Descriptions

Clear PR descriptions and well-documented code make the review process smoother. When you clearly explain what the code does and any challenges faced, reviewers can more easily understand the changes and provide more relevant feedback.

How to Implement:

• Ensure each pull request includes a description of the changes and the context behind them.

• Encourage yourself to include details on tests, performance impacts, and dependencies.

• Maintain documentation for all significant changes, ensuring easy understanding for current and future work.

Following these best practices makes code reviews easier, more consistent, and more useful for you and your team.

Four Common Approaches to Code Review

Each team adopts a different code review approach depending on its size, needs, and workflow. Below, we explore the four most common strategies and how they work.

1. Pair Programming

Pair programming involves two developers coding together, reviewing and enhancing each other’s work as they go. One developer, the "driver," writes the code while the other, the "navigator," reviews it, offers suggestions, and helps steer the process. This method not only enables real-time code review but also facilitates continuous collaboration.

Pros:

• Instant feedback and collaboration.

• Encourages deeper problem-solving and knowledge transfer.

Cons:

• It can be resource-intensive and tiring for long sessions.

• Might not scale well for larger teams or complex codebases.

2. Over-the-Shoulder Reviews

In an over-the-shoulder review, one developer observes another as they go through their code. This review type is typically informal and occurs in real-time, often in a face-to-face setting. It allows for quick discussions and immediate feedback during the development process.

Pros:

• Quick, informal feedback.

• Good for small teams or when you need immediate guidance.

Cons:

• It may not be efficient for large codebases.

• Limited tracking of changes and feedback.

3. Tool-Assisted Reviews

Tool-assisted reviews automate tasks like syntax checks and testing, streamlining the review process. Entelligence AI takes this a step further by providing real-time, context-driven feedback and smarter bug detection. Integrated seamlessly with GitHub, GitLab, and other platforms, Entelligence AI helps you and your team focus on high-level tasks while automating repetitive checks, ensuring consistent code quality, and faster review cycles.

Pros:

• Faster and more automated checks.

• Integrated with Continuous Integration (CI) and Continuous Deployment (CD) pipelines.

Cons:

• Can miss the nuanced understanding that manual reviewers bring.

• Tools alone can’t replace human insight into architecture and design.

4. Email Pass-Around

This method involves sharing code via email with teammates for review. It’s often used in smaller teams or informal setups where you share your code in a less structured manner. The feedback is typically provided in response to email threads or comments.

Pros:

• Flexible and non-intrusive.

• Simple and works well in smaller teams with fewer tools.

Cons:

• Disorganized and harder to track.

• Can lead to fragmented feedback, making it difficult to manage.

With these approaches in mind, it's time to have a look at some of the common challenges in your code review process.

Also Read: Introducing Entelligence Engineering Leaderboard: a real time scoreboard for developers

Common Challenges in Code Reviews 

Code reviews, while essential, often come with hurdles of their own. Below, we’ll explore the most common challenges that impact the effectiveness of the review process. 

1. Time Consumption: One of the biggest challenges in code reviews is the time they require. Without a structured approach, reviews can drag on, leading to burnout and inefficiency.

2. Inconsistent Quality: Varying standards among reviewers can lead to missed issues, inconsistent code quality, and confusion among you and your team.

3. Psychological Barriers: You and your team may be hesitant to give or receive feedback due to fears of criticism or misunderstandings. This lack of psychological safety can diminish the effectiveness of code reviews.

Code reviews will always have their challenges, but with the right support, like Entelligence AI, they can become faster, smoother, and more effective.

Also Read: Entelligence vs. Greptile: The Ultimate AI Code Review Showdown

Enhance Your Code Reviews with Entelligence AI

Code reviews are essential, but they often drain time with repetitive checks, inconsistent feedback, and missed issues that slip into production. You and your team want to focus on building great features, not chasing minor errors or re-explaining standards across every pull request.

Entelligence AI removes that friction by combining automation with intelligence. Instead of slowing your work down, it speeds reviews up with actionable, context-aware insights, making every review faster, clearer, and more consistent.

• Enhanced Code Quality & Security: Real-time scans, static analysis, and auto-remediations prevent bugs and vulnerabilities.

• Automatic Bug Detection: Flags errors instantly, reducing manual review effort.

• Smart Suggestions: Offers improvements based on code patterns and best practices.

• Seamless Integration: Works with GitHub, GitLab, and more; fitting naturally into your CI/CD workflow.

• Faster Review Cycles: Automates minor checks and accelerates feedback loops.

• Consistency Across Reviews: Ensures standards are applied uniformly across teams.

By taking over repetitive work, Entelligence AI transforms code reviews from a bottleneck into a driver of productivity, quality, and collaboration.

Conclusion

Creating an efficient code review process takes time, but the payoff is substantial. By implementing clear processes, utilizing automated tools, and promoting a positive review culture, you can produce high-quality, maintainable software. 

Code reviews then shift from being bug-hunting exercises to collaborative sessions that drive learning and improvement.

With Entelligence AI, you can take this a step further. Its AI-powered automation and intelligent insights help reduce friction, save time, and elevate review quality. Start a free trial today and see how Entelligence AI transforms your development process.

Frequently Asked Questions

Q. What does a good code review look like?

A good code review offers clear, actionable feedback on code quality, performance, and security. It encourages collaboration, maintains a positive tone, and facilitates knowledge sharing. It’s constructive, focused on improvement, and ensures adherence to coding standards and best practices.

Q. What are the 7 steps to review code?

The seven steps include: understanding the code’s purpose, reviewing code structure and style, checking functionality, evaluating performance, assessing security, ensuring readability, and providing actionable feedback. These steps ensure thorough reviews that enhance code quality and ensure long-term maintainability.

Q. Can ChatGPT do a code review?

ChatGPT can flag syntax issues and suggest improvements, but it lacks project-specific context. Tools like Entelligence.ai bridge that gap with context-aware, holistic insights, making reviews faster and more reliable. Human judgment remains essential, but pairing it with Entelligence delivers stronger, streamlined code reviews.

Q. What makes a code review bad, and how can one avoid them?

Bad code reviews are vague, overly critical, or lacking constructive feedback. They can be avoided by maintaining a positive tone, focusing on specific issues, offering solutions, and ensuring reviews are clear, actionable, and consistent across the team with clear guidelines.

Q. What are some secrets to doing fast code reviews?

Fast code reviews require keeping pull requests small, focusing on key issues, and automating basic checks with tools. Having clear review guidelines, limiting distractions, and distributing the workload can help speed up the process while maintaining quality.