Code Review with ChatGPT

Code review is a critical part of the software development process that ensures code quality, catches bugs early, and promotes knowledge sharing among team members. ChatGPT can significantly streamline this process by providing detailed feedback, identifying potential issues, and suggesting improvements across multiple dimensions—from security vulnerabilities to performance optimizations.

This guide will help you craft effective prompts for code reviews using ChatGPT, whether you're reviewing your own code, preparing for peer reviews, or learning best practices. You'll learn how to structure your review requests, what context to provide, and how to get the most actionable feedback from AI-assisted code reviews.

Best Practices

1. Provide Context

Always include relevant context when asking for a code review:

• The programming language and version
• Framework or libraries being used
• Purpose of the code
• Any specific concerns or areas to focus on

When reviewing code for refactoring opportunities, consider checking out our code refactoring guide for complementary strategies.

2. Break Down Large Reviews

For better results:

• Split large codebases into smaller, focused segments
• Review one component or function at a time
• Prioritize critical or complex sections

3. Ask Specific Questions

Guide the review by asking specific questions about:

• Code efficiency
• Security concerns
• Best practices adherence
• Potential edge cases
• Performance implications

Example Prompts

Basic Code Review

Please review this Python function that calculates factorial:

def factorial(n):
    if n < 0:
        return None
    if n == 0:
        return 1
    return n * factorial(n-1)

Focus on:
1. Error handling
2. Performance
3. Edge cases
4. Coding standards

Security Review

Review this Node.js authentication middleware for security vulnerabilities:

const auth = async (req, res, next) => {
    try {
        const token = req.header('Authorization').replace('Bearer ', '')
        const decoded = jwt.verify(token, process.env.JWT_SECRET)
        const user = await User.findOne({ _id: decoded._id, 'tokens.token': token })
        if (!user) throw new Error()
        req.user = user
        next()
    } catch (e) {
        res.status(401).send({ error: 'Please authenticate.' })
    }
}

Performance Review

Analyze this React component for performance optimization opportunities:

const UserList = ({ users }) => {
    const [filteredUsers, setFilteredUsers] = useState(users)
    const [searchTerm, setSearchTerm] = useState('')

    useEffect(() => {
        setFilteredUsers(
            users.filter(user =>
                user.name.toLowerCase().includes(searchTerm.toLowerCase())
            )
        )
    }, [searchTerm, users])

    return (
        <div>
            <input
                type="text"
                value={searchTerm}
                onChange={(e) => setSearchTerm(e.target.value)}
            />
            {filteredUsers.map(user => (
                <UserCard key={user.id} user={user} />
            ))}
        </div>
    )
}

Common Pitfalls

1. Lack of Context

   • Not specifying the programming language
   • Omitting important dependencies or requirements
   • Not explaining the purpose of the code

2. Too Much Code

   • Sending entire files or multiple components
   • Not focusing on specific areas of concern
   • Overwhelming the model with unnecessary details

3. Vague Requests

   • Asking for general review without specific focus
   • Not specifying what aspects need attention
   • Not providing acceptance criteria

Advanced Tips

1. Iterative Reviews

Break down the review process into multiple steps:

1. Initial review for basic issues
2. Deep dive into specific concerns
3. Follow-up on implemented changes

2. Comparative Analysis

Ask ChatGPT to compare different approaches. This is particularly useful when evaluating architectural decisions—learn more in our architecture design guide:

Which implementation is better for handling user authentication?

Approach 1:
[code snippet 1]

Approach 2:
[code snippet 2]

Consider:
- Security
- Maintainability
- Performance
- Error handling

3. Documentation Review

Use ChatGPT to review documentation completeness:

Review these function comments for clarity and completeness:

/**
 * Processes user data and updates the database
 * @param {Object} userData - The user data to process
 * @returns {Promise<boolean>} - Success status
 */
async function processUserData(userData) {
    // Implementation
}

Conclusion

Effective code reviews with ChatGPT require clear communication, proper context, and specific focus areas. By following these guidelines and using the example prompts as templates, you can get more valuable and actionable feedback for your code reviews.

Once you've reviewed and refined your code, you might want to explore our code generation guide to learn how to generate high-quality code from scratch using ChatGPT.