Table of contents

• Definition and purpose of code reviews
• Benefits of code reviews
• Code review vs. pair programming
• Preparing for code reviews
• The code review process
• AI-powered code reviews with Diamond
• Best practices for effective code reviews
• Frequently asked questions

Code reviews are an integral part of the software development process, serving as a checkpoint to ensure quality, consistency, and collaborative knowledge sharing within a development team. This guide aims to provide an extensive introduction to the principles and practices of effective code reviews, integrating knowledge from industry studies, best practices from top tech companies, and insights into the use of modern tools like Graphite and Diamond, which build upon the foundation of platforms such as GitHub.

Definition and purpose of code reviews

A code review is a stage in the software development workflow where the source code changes made by a developer are examined by one or more peers before the code is merged into the main codebase. The primary objectives are to:

1. Ensure quality: Detect and fix defects early in the development cycle, reducing the cost of bug fixes and ensuring high-quality output.

2. Maintain consistency: Align the new code with existing design patterns and coding standards to maintain a coherent codebase.

3. Share knowledge: Facilitate knowledge transfer among team members, promoting a deeper understanding of the codebase and development practices.

4. Improve skills: Provide an opportunity for developers to receive constructive feedback on their coding practices, leading to skill enhancement.

Benefits of code reviews

The benefits of code reviews are well-documented, with studies showing a significant reduction in defect density and improvements in code quality. For instance, a SmartBear study of a Cisco Systems programming team suggests that reviewing fewer than 400 lines of code (LOC) at a time leads to a higher defect discovery rate, with optimal inspection rates under 500 LOC per hour.

Code review vs. pair programming

While code reviews involve scrutinizing code after it has been written, pair programming is a real-time collaboration where two developers write code together. Both practices aim to improve code quality and facilitate learning but differ in their execution and focus.

Modern development teams often combine these approaches with AI-powered tools like Diamond to enhance both practices—providing real-time AI feedback during pair programming sessions and comprehensive automated analysis during code reviews.

Preparing for code reviews

Before diving into code reviews, it's essential to:

• Establish clear coding standards and guidelines.

• Ensure reviewers have a comprehensive understanding of the codebase and the functionality being implemented or altered.

• Utilize tools that enhance the code review process. For example, Graphite's pattern of stacked PRs for more organized and manageable code reviews on top of platforms like GitHub, combined with Diamond's AI-powered analysis for immediate, codebase-aware feedback.

The code review process

A typical code review process involves several stages:

1. Selection of reviewers: The code author selects relevant reviewers, considering expertise and domain knowledge.

2. Code examination: Reviewers inspect the code for defects, readability, and maintainability, often using checklists as a guide.

3. Feedback: Comments and suggestions are provided to the author, who then works on integrating the feedback.

4. Approval and merge: Once all parties are satisfied, the code is approved for merging into the main codebase.

AI-powered code reviews with Diamond

Modern code review workflows are increasingly incorporating AI tools to enhance efficiency and consistency. Diamond, Graphite's AI code review tool, represents a significant advancement in automated code analysis:

Key features of Diamond:

• Codebase-aware analysis: Unlike generic code checkers, Diamond understands your entire codebase context, enabling more accurate and relevant feedback
• Real-time feedback: Provides immediate suggestions on pull requests, reducing review cycle times
• Customizable rules: Teams can configure Diamond to enforce specific coding standards and patterns
• One-click fixes: Offers suggested code improvements that can be applied with a single click
• Privacy-focused: Doesn't store or train on your code, ensuring proprietary information remains secure

Integration with Graphite's workflow:

Diamond works seamlessly with Graphite's stacked PR approach, providing AI analysis on each individual change while maintaining the benefits of smaller, more focused reviews. This combination allows teams to:

• Catch bugs and logic errors early in the development process
• Maintain consistent coding standards across all pull requests
• Reduce the cognitive load on human reviewers by automating routine checks
• Focus human expertise on complex architectural and design decisions

Best practices for effective code reviews

The effectiveness of code reviews is heightened by following best practices, such as:

1. Reviewing small increments: Smaller, more frequent reviews are more effective than large, infrequent ones. Graphite's stacked PR approach naturally encourages this practice by breaking large changes into manageable pieces.

2. Providing constructive feedback: Comments should be specific, actionable, and focused on the code rather than the coder.

3. Emphasizing a learning culture: Reviews should be seen as opportunities for growth, not just error detection.

4. Leveraging AI assistance: Use tools like Diamond to automate routine checks and focus human reviewers on complex architectural decisions and business logic.

5. Combining human and AI insights: While AI tools can catch many issues automatically, human reviewers should focus on code design, maintainability, and domain-specific knowledge that requires contextual understanding.

Code reviews are more than just a quality check; they are a cultural practice that, when implemented effectively, contribute significantly to the health of the codebase and the development team. By combining traditional review practices with modern tools like Graphite for workflow management and Diamond for AI-powered analysis, teams can create a more efficient and comprehensive review process that maintains high code quality while reducing the time and effort required for manual reviews.

The future of code reviews lies in the thoughtful integration of human expertise with AI assistance, ensuring that both the technical and cultural benefits of code review are preserved while embracing the efficiency gains that modern tooling provides.

Frequently asked questions

What are the three types of code review?

There are three common approaches: formal inspections, lightweight reviews, and change-based (pull request) reviews. Formal inspections are structured and documentation-heavy; lightweight reviews are fast, informal feedback mechanisms like pair programming or over-the-shoulder checks; change-based reviews focus on diffs before merging.

Who should do code reviews?

Peer developers familiar with the codebase should perform reviews, while senior engineers or domain experts should review critical or architectural changes. Include specialist reviewers (security, performance) and automated tools as needed to catch routine issues.

What to expect in a code review?

Expect the author to provide context and a diff, reviewers to check correctness, readability, tests, and design, and automated checks to run where configured. Feedback is iterated until reviewers approve and the change is merged.

How important are code reviews?

Code reviews are essential for catching defects early, improving design and maintainability, and spreading knowledge across the team. They add overhead, but well-structured reviews and good tooling typically deliver net benefits in quality, reduced technical debt, and safer releases.