Bug fixes

Bug fixing with Runbooks involves using AI to analyze error patterns, understand root causes, and implement comprehensive fixes across your codebase. Unlike manual bug fixing that addresses issues one at a time, Runbooks can identify patterns and fix similar bugs systematically across multiple files and repositories.

When to use

Ideal scenarios

• Systematic bug patterns: When the same bug appears in multiple places

• Legacy vode issues: Fixing bugs in poorly documented legacy code

• Security vulnerabilities: Addressing security issues consistently across the codebase

• Performance bugs: Identifying and fixing performance bottlenecks

• Cross-repository issues: Bugs that span multiple services or repositories

Perfect for teams that

• Need to fix bugs consistently across large codebases

• Want to prevent similar bugs from reoccurring

• Have limited time for manual bug investigation

• Need to ensure comprehensive fixes without missing edge cases

Two approaches

1. Template-based bug fixing

Use pre-built templates for common bug patterns from the runbooks library.

Common Bug Fix Templates Available:

• Memory leak prevention: Fixes event listener cleanup and reference management

• SQL injection prevention: Updates database queries to use parameterized statements

• XSS vulnerability fixes: Sanitizes user input and output across applications

• Race condition resolution: Implements proper synchronization and state management

• Null pointer exception fixes: Adds defensive programming patterns

2. One-Shot Bug Fixing (without Templates)

For unique or specific bugs, use one-shot mode to get immediate diagnosis and fixes.

One-Shot Bug Fixing Deep Dive

One-shot mode is perfect for urgent bug fixes and unique issues that don't fit standard templates. Here's how it works:

How One-Shot Mode Works

Immediate Analysis and Fix:

1. Direct Problem Description: Describe the bug you're experiencing

2. Instant AI Analysis: AI immediately analyzes your codebase for the issue

3. Root Cause Identification: Identifies the underlying cause and related issues

4. Comprehensive Fix: Implements a complete solution including edge cases

5. Automatic Execution: Runs the fix immediately without requiring step-by-step approval

When to Use One-Shot Mode

Production Issues:

"Our checkout process is failing with a 500 error when users have more than 10 items in their cart. The error logs show 'Cannot read property length of undefined' in the order calculation service."

Performance Emergencies:

"Our application memory usage keeps growing until it crashes. It seems related to WebSocket connections not being properly cleaned up when users disconnect."

Security Incidents:

"We discovered that user input in our comment system isn't being properly sanitized, potentially allowing XSS attacks. We need to fix this immediately across all user input points."

One-Shot Example: Memory Leak Fix

Problem Description:

"Our React application has a memory leak. Components are not cleaning up event listeners and timers when they unmount, causing memory usage to grow continuously."

One-Shot AI Analysis:

1. Codebase scan: Scans all React components for event listeners and timers

2. Pattern detection: Identifies components missing cleanup in useEffect

3. Impact assessment: Determines which components are most problematic

4. Fix generation: Creates comprehensive cleanup implementation

Immediate Fix Implementation:

// Before: Memory leak
useEffect(() => {
  window.addEventListener('resize', handleResize);
  const timer = setInterval(updateData, 1000);
}, []);

// After: Proper cleanup
useEffect(() => {
  const handleResize = () => { /* handler logic */ };
  window.addEventListener('resize', handleResize);
  const timer = setInterval(updateData, 1000);

  return () => {
    window.removeEventListener('resize', handleResize);
    clearInterval(timer);
  };
}, []);

One-Shot benefits:

• Speed: Immediate diagnosis and fix without needing any user interactions

• Comprehensive: Fixes all instances of the pattern, not just the reported case

• Prevention: Adds safeguards to prevent similar issues in the future

• In Slack context: Can be triggered from Slack in-context

Real-World Bug Fixing Examples

Example 1: Cross-Browser Compatibility Bug

Problem report:

"Our drag and drop functionality works in Chrome but fails in Safari and Firefox. Users report that items don't drop correctly and sometimes disappear."

Root cause analysis:

1. Browser API differences: Identifies Safari-specific event handling requirements

2. Polyfill requirements: Determines which polyfills are needed

3. Event model differences: Finds inconsistencies in drag/drop event handling

4. Testing strategy: Creates cross-browser testing approach

Systematic fix:

// Before: Chrome-only implementation
element.addEventListener('drop', (e) => {
  const data = e.dataTransfer.getData('text');
  // Chrome-specific handling
});

// After: Cross-browser compatible
element.addEventListener('drop', (e) => {
  e.preventDefault();
  const data = e.dataTransfer.getData('text/plain') ||
               e.dataTransfer.getData('text');

  // Safari fallback handling
  if (!data && e.dataTransfer.files.length > 0) {
    // Handle file drop for Safari
  }

  // Cross-browser drop handling
});

Example 2: State Management Bug

Problem report:

"Users are experiencing stale data in our dashboard. When they update settings in one component, other components don't reflect the changes until they refresh the page."

Root cause analysis:

1. State flow mapping: Maps how data flows through the application

2. Update pattern analysis: Identifies where state updates aren't propagating

3. Cache invalidation issues: Finds stale caching problems

4. Race condition detection: Identifies timing-related state issues

Systematic fix:

• Implements proper state invalidation

• Adds reactive data updates

• Fixes cache management

• Includes state debugging tools

Example 3: API error handling bug

Problem report:

"Our application crashes when the API returns unexpected error formats. Some services return errors differently, and our error handling doesn't account for all variations."

Systematic fix:

1. Error Format Analysis: Catalogs all possible error response formats

2. Handler Standardization: Creates consistent error handling patterns

3. Fallback Implementation: Adds graceful degradation for unknown errors

4. Monitoring Integration: Adds error tracking and alerting

---

See also

• Improving readability

• Improving code coverage