Code Review

Code Review - Systematic Code Quality Analysis

When to use this skill

• Reviewing pull requests before merging to main branch
• Conducting peer code reviews for team members
• Performing self-reviews before submitting code for review
• Auditing code quality and standards compliance
• Checking for security vulnerabilities and bad practices
• Verifying adequate test coverage exists
• Assessing performance implications of changes
• Evaluating architectural and design decisions
• Ensuring consistency with project coding standards
• Providing constructive feedback to improve code quality
• Reviewing critical business logic or sensitive operations
• Checking for common anti-patterns and code smells

When to use this skill

• Reviewing pull requests, feature implementations, or code changes before merging to ensure quality, maintainability, and adherence to best practices.
• When working on related tasks or features
• During development that requires this expertise

Use when: Reviewing pull requests, feature implementations, or code changes before merging to ensure quality, maintainability, and adherence to best practices.

Core Principles

1. Review for Understanding First - Before suggesting changes, ensure you understand the intent and context
2. Be Specific and Actionable - Point to exact lines with concrete suggestions
3. Balance Positives with Improvements - Acknowledge good patterns while suggesting enhancements
4. Focus on Impact - Prioritize critical issues (security, correctness) over style preferences
5. Educate, Don't Just Correct - Explain why a change matters

Review Checklist

1. Correctness & Logic

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✓ Does the code do what it claims to do?
✓ Are edge cases handled (null, empty, boundary values)?
✓ Are there potential race conditions or timing issues?
✓ Is error handling appropriate and complete?
✓ Are assumptions validated?

2. Security

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✓ Input validation on all user-provided data?
✓ SQL injection, XSS, CSRF protections?
✓ Secrets/credentials properly secured (env vars, not hardcoded)?
✓ Authentication and authorization checks?
✓ Rate limiting on public endpoints?

3. Performance

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✓ N+1 query problems?
✓ Unnecessary database calls or API requests?
✓ Memory leaks (event listeners, subscriptions)?
✓ Proper pagination for large datasets?
✓ Efficient algorithms (avoid O(n²) when O(n log n) possible)?

4. Maintainability

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✓ Clear, descriptive names for variables/functions?
✓ Functions do one thing well (Single Responsibility)?
✓ DRY - no copy-paste duplication?
✓ Magic numbers replaced with named constants?
✓ Complex logic explained with comments?

5. Testing

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✓ Tests cover happy path and error cases?
✓ Tests are deterministic (no flaky tests)?
✓ Edge cases tested?
✓ Integration points mocked/stubbed appropriately?
✓ Test names describe what they verify?

6. Code Style & Standards

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✓ Consistent with project conventions?
✓ Follows language idioms?
✓ No unused imports or dead code?
✓ Proper error types thrown/returned?
✓ TypeScript types specific (not 'any')?

Review Process

Step 1: High-Level Review

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1. Read PR description and linked issues
2. Understand the "why" behind changes
3. Scan file list - does scope match description?
4. Check for missing files (tests, migrations, docs)

Step 2: Deep Code Review

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1. Review critical paths first (security, data integrity)
2. Check test coverage and quality
3. Look for architectural issues
4. Review error handling
5. Check for performance concerns

Step 3: Provide Feedback

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Format: [SEVERITY] Issue - Specific suggestion

Example:
[CRITICAL] SQL Injection vulnerability on line 45
- Use parameterized queries instead of string concatenation
- Change: `query = f"SELECT * FROM users WHERE id = {user_id}"`
- To: `query = "SELECT * FROM users WHERE id = ?"` with params

[SUGGESTION] Consider extracting this 50-line function into smaller pieces
- Lines 100-150 could be broken into:
  - `validateInput()` (lines 100-120)
  - `processData()` (lines 121-140)  
  - `formatOutput()` (lines 141-150)

Feedback Severity Levels

• [CRITICAL] - Security issue, data loss risk, broken functionality
• [MAJOR] - Performance problem, poor error handling, incorrect logic
• [MINOR] - Code smell, maintainability concern, style inconsistency
• [SUGGESTION] - Nice-to-have improvement, alternative approach
• [PRAISE] - Well-done pattern worth highlighting

Example Code Review

Pull Request: Add user authentication endpoint

Review Comments:

[CRITICAL] Missing authentication on password change endpoint (line 67)

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// Current - No auth check
app.post('/change-password', (req, res) => {
  const { userId, newPassword } = req.body;
  updatePassword(userId, newPassword);
});

// Should be:
app.post('/change-password', requireAuth, (req, res) => {
  // Only allow users to change their own password
  if (req.user.id !== req.body.userId) {
    return res.status(403).json({ error: 'Forbidden' });
  }
  const { newPassword } = req.body;
  updatePassword(req.user.id, newPassword);
});

[MAJOR] Password not hashed before storage (line 23)

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// Never store plain text passwords
await db.users.update({ password: req.body.password }); // ❌

// Use bcrypt or argon2
const hashedPassword = await bcrypt.hash(req.body.password, 10);
await db.users.update({ passwordHash: hashedPassword }); // ✅

[MINOR] Magic number for token expiry (line 45)

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const token = jwt.sign(payload, secret, { expiresIn: 3600 }); // ❌

// Use named constant
const TOKEN_EXPIRY_SECONDS = 60 * 60; // 1 hour
const token = jwt.sign(payload, secret, { expiresIn: TOKEN_EXPIRY_SECONDS }); // ✅

[PRAISE] Excellent input validation (lines 12-20) The zod schema here is comprehensive and includes all necessary checks. This prevents malformed data from reaching the database.

Common Anti-Patterns to Flag

1. Silent Failures

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// Bad - errors disappear
try {
  await criticalOperation();
} catch (e) {
  console.log('oops'); // ❌
}

// Good - proper error handling
try {
  await criticalOperation();
} catch (e) {
  logger.error('Critical operation failed', { error: e, context: {...} });
  throw new CriticalOperationError('Failed to process', { cause: e });
}

2. Callback Hell / Pyramid of Doom

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// Bad
getData((data) => {
  processData(data, (result) => {
    saveResult(result, (saved) => {
      // 3+ levels deep ❌
    });
  });
});

// Good - use async/await
const data = await getData();
const result = await processData(data);
const saved = await saveResult(result);

3. God Functions

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// Bad - function doing too much
function handleUserRequest(req) {
  // 200 lines of validation, processing, formatting, saving ❌
}

// Good - split responsibilities
function handleUserRequest(req) {
  const validated = validateRequest(req);
  const processed = processUserData(validated);
  const formatted = formatResponse(processed);
  return saveAndRespond(formatted);
}

When to Block vs Approve with Comments

Block merge (Request Changes):

• Security vulnerabilities
• Data loss risks
• Broken functionality
• Missing critical tests
• Major performance issues

Approve with comments:

• Style improvements
• Refactoring suggestions
• Minor performance optimizations
• Documentation enhancements
• Nice-to-have tests

Automated Checks

Before manual review, ensure automated checks pass:

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✓ Linting (ESLint, Pylint, etc.)
✓ Type checking (TypeScript, mypy)
✓ Unit tests passing
✓ Integration tests passing
✓ Code coverage meets threshold
✓ Security scanning (SAST)
✓ Dependency vulnerability scanning

Review Response Template

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## Summary
[High-level assessment of the PR]

## Critical Issues
- [List blocking issues]

## Major Concerns  
- [List important but not blocking issues]

## Suggestions
- [List nice-to-have improvements]

## Positive Highlights
- [Call out well-done patterns]

## Questions
- [Clarifying questions about intent or approach]

## Approval Status
- [ ] Approved - ready to merge
- [ ] Approved with minor comments
- [ ] Request changes - blocking issues need resolution

Resources

• Google Code Review Guidelines
• Conventional Comments
• Code Review Best Practices

Remember: The goal is to improve code quality while maintaining team morale. Be thorough but respectful, specific but not pedantic, and always explain the "why" behind suggestions.