Is AI the future of code reviews?

We review code to ensure quality, consistency, and maintainability but with AI becoming more integrated into development workflows, can AI-driven code reviews really replace the human touch?

In this article, I'll explore how AI is transforming code reviews, the benefits it brings to the table, and why, despite all the hype, human oversight is still necessary.

Why code reviews exist

Code reviews are an essential practice in modern software development. The process allows teams to catch bugs, ensure good coding standards are kept, and improve the overall quality of codebases.

Senior engineers often act as mentors during these reviews, sharing feedback with junior developers and ensuring that work aligns with the goals of the engineering team, and the company at whole.

But the code review process can be time-consuming. It requires engineers to read through, understand, and assess the impact of new code on existing systems.  As software projects grow in complexity, the amount of code that needs reviewing increases, and this often slows down the overall development cycle.

Enter AI-driven code review tools.

How AI is disrupting the code review process

AI-driven code review tools are designed to automate parts of the code review process. By leveraging machine learning models trained on large codebases, these tools can identify common bugs, potential security vulnerabilities, and adherence to coding standards much faster than a human reviewer could.

In fact, here's what AI can already do:

1. Automate detection of bugs
   AI tools like Snyk and Codiga analyze code in real-time to detect potential bugs and issues. These tools are trained on millions of lines of code and can spot certain types of problems with a reasonable level of accuracy.

2. Make bug reports more readable
   AI powered bug reporting software like capture.dev can take complicated error messages and stack traces from a running application, and convert them into a more easy to read format to save engineering teams time when it comes to tracking down the source of problems.

3. Enforce code standards
   AI tools can be programmed to enforce style guides and coding conventions, making sure that code remains consistent across a team. This reduces the need for humans to focus on nit-picky style issues and allows them to focus on more meaningful aspects of the review.

4. Predict code quality issues
   Some AI tools, like sourcery,  can predict areas of code that are likely to become problematic in the future, such as sections of code that are prone to errors, difficult to maintain, or likely to introduce technical debt.

AI powered code review tools like Sourcery can detect complexity in code and even suggest improvements.

The benefits of AI in code reviews

At a surface level, AI-driven code review tools offer several advantages, which can make them an attractive option for development teams looking to improve code quality while reducing the time spent on manual reviews.  

Here are some of the key benefits:

• Faster feedback loops
  AI can analyze code instantly, providing feedback much faster than human reviewers. This speeds up the development process so teams can iterate more quickly.

• Reduced reviewer fatigue
  It's easy for human reviewers to get bogged down by minor issues, and lose sight of the bigger picture. AI can handle these repetitive tasks, freeing engineers to focus on the more critical aspects of the review.

• Consistency
  AI can enforce coding standards and best practices consistently across the entire team, ensuring that no corner of the codebase is left unchecked for style or security issues.

• Scalability
  As teams and codebases grow, scaling the human review process becomes challenging. AI can easily scale to handle increased code volume without sacrificing speed or quality.

Why human reviewers are still essential

Despite all the benefits, I don't believe AI is at the point where we can completely eliminate human code reviewers anytime soon. Here's why:

1. It lacks contextual understanding
   AI can't fully grasp the context in which code is written. It can identify patterns, but it doesn't understand the business logic or the product goals behind a piece of code. I'd go as far as to say understanding the why behind why a piece of code exists is something only humans can do.

2. Creativity is important
   Code review isn't just about finding bugs — it's also about improving code quality and solving problems in more efficient or innovative ways. AI can spot issues, but it can’t suggest creative solutions or refactor code to improve performance or readability in ways that a human with an understanding of the goals of the project can.

3. It can't replace good mentorship
   One of the most valuable aspects of code reviews is the opportunity for mentorship and for senior engineers to offer feedback and explanations that help junior engineers grow.  AI might catch bugs, but it can't provide the nuanced explanations or context needed for a developer to truly understand and learn from their mistakes. Without the human element, this critical learning opportunity would be lost.

Think of AI as an enhancement, not a replacement

AI-driven code reviews are a powerful tool that can significantly improve the speed and quality of software development, but they are not a replacement for human engineers.

Instead, AI should be seen as an enhancement—automating the repetitive, easily identifiable issues and freeing up engineers to focus on the higher-level thinking and problem-solving that machines can't do.

If you'd like to discover how AI can help you spend less time recording, reporting and investigating bugs, you may be interested in capture.dev - an AI powered bug reporting tool for automating bug reporting so your engineering team can spend less time debugging, and more time building.