Performance Optimization

Blurs AI helps identify performance bottlenecks and suggests optimizations to improve your application's speed and efficiency.

Code Analysis

Identifying Bottlenecks

Submit code for performance analysis:

Review this code for performance issues and suggest optimizations: [paste code]

Blurs AI will identify:

• Slow algorithms
• Inefficient loops
• Memory-intensive operations
• Unnecessary re-renders
• Blocking operations

Common Optimizations

React Performance

Preventing Unnecessary Re-renders

This component re-renders too often. How can I optimize it? [paste code]

Suggestions may include:

• Using React.memo
• Memoizing callbacks with useCallback
• Memoizing values with useMemo
• Splitting components

Optimizing Lists

I'm rendering a large list. How can I improve performance? [paste code]

Database Queries

Query Optimization

Review this database query for performance issues: [paste SQL or ORM code]

Blurs AI can suggest:

• Adding indexes
• Avoiding N+1 queries
• Using joins instead of multiple queries
• Query result caching

Bundle Size Optimization

Reducing Bundle Size

My bundle size is too large. Help me optimize it: [paste config]

Suggestions include:

• Code splitting
• Tree shaking
• Removing unused dependencies
• Dynamic imports

API Performance

Optimizing API Calls

This API endpoint is slow. How can I improve it? [paste code]

Optimization Workflow

Step 1: Identify Issues

Use performance profiling tools or Blurs AI to identify slow areas:

• Slow page loads
• Laggy interactions
• High memory usage
• Slow API responses

Step 2: Analyze Code

Submit problematic code to Blurs AI:

• Get detailed analysis
• Understand the root cause
• Learn why it's slow

Step 3: Apply Optimizations

Implement suggested optimizations:

• Test each change
• Measure improvements
• Verify functionality still works

Step 4: Monitor Results

Track performance metrics:

• Before and after comparisons
• Real user metrics
• Server resource usage

Best Practices

Measure First

Always measure performance before optimizing:

• Use profiling tools
• Set baseline metrics
• Identify actual bottlenecks

Optimize Incrementally

Make one change at a time:

• Test each optimization
• Measure the impact
• Keep what works

Balance Readability

Don't sacrifice code clarity:

• Optimize only where needed
• Maintain code readability
• Document complex optimizations

Common Optimization Patterns

Memoization

Optimize this expensive calculation with memoization: [paste code]

Lazy Loading

Convert this to lazy loading to improve initial load time: [paste code]

Debouncing/Throttling

Add debouncing to this search input: [paste code]

Virtual Scrolling

Implement virtual scrolling for this large list: [paste code]

Performance Metrics

Key Metrics to Track

• Load Time - Initial page load
• Time to Interactive - When page becomes usable
• First Contentful Paint - First content appears
• Largest Contentful Paint - Main content loads
• Cumulative Layout Shift - Visual stability

Monitoring Tools

• Browser DevTools
• Lighthouse
• WebPageTest
• Real User Monitoring (RUM)

Advanced Optimizations

Code Splitting

Implement code splitting for this large application: [paste code]

Service Workers

Add a service worker for offline support and caching: [paste code]

Caching Strategies

Implement caching for this API: [paste code]

Database Indexing

Suggest indexes for these queries: [paste queries]

Next Steps

• Review Best Practices
• Check API Reference
• Learn more about Code Generation