Performance analysis based on Core Web Vitals

Analyzes application performance from a user experience perspective and quantifies experience improvements from optimizations. Calculates UX scores based on Core Web Vitals and proposes prioritized optimization strategies.

UX Performance Score

text
User Experience Score: B+ (78/100)
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⏱️ Core Web Vitals
├─ LCP (Loading): 2.3s [Good] Target<2.5s ✅
├─ INP (Interaction): 95ms [Good] Target<200ms ✅
├─ CLS (Visual Stability): 0.08 [Good] Target<0.1 ✅
├─ FCP (First Paint): 1.8s [Good] Target<1.8s ✅
├─ TTFB (Server): 450ms [Needs Work] Target<200ms ⚠️
└─ TTI (Interactive): 3.5s [Needs Work] Target<3.8s ⚠️

📊 Perceived Speed
├─ Initial Load: 2.3s [Industry avg: 3.0s]
├─ Page Navigation: 1.1s [Industry avg: 1.5s]
├─ Search Results: 0.8s [Industry avg: 1.2s]
├─ Form Submission: 1.5s [Industry avg: 2.0s]
└─ Image Loading: Lazy loading implemented ✅

😊 User Satisfaction Prediction
├─ Bounce Rate: 12% (Industry avg: 20%)
├─ Completion Rate: 78% (Target: 85%)
├─ NPS Score: +24 (Industry avg: +15)
└─ Return Rate: 65% (Target: 70%)

📊 User Experience Impact
├─ 0.5s faster display → -7% bounce rate
├─ 5% bounce reduction → +15% session length
├─ Search improvement → +15% time on site
└─ Overall UX improvement: +25%

🎯 Expected Improvement Effects (Priority Order)
├─ [P0] TTFB improvement (CDN) → LCP -0.3s = +15% perceived speed
├─ [P1] JS bundle optimization → TTI -0.8s = -20% interactive time
├─ [P2] Image optimization (WebP) → -40% transfer = -25% load time
└─ [P3] Cache strategy → 50% faster repeat visits

Usage

bash
# Comprehensive UX score analysis
find . -name "*.js" -o -name "*.ts" | xargs wc -l | sort -rn | head -10
"Calculate UX performance score and evaluate Core Web Vitals"

# Performance bottleneck detection
grep -r "for.*await\|forEach.*await" . --include="*.js"
"Detect async processing bottlenecks and analyze UX impact"

# User experience impact analysis
grep -r "addEventListener\|setInterval" . --include="*.js" | grep -v "removeEventListener\|clearInterval"
"Analyze performance impact on user experience"

Basic Examples

bash
# Bundle size and load time
npm ls --depth=0 && find ./public -name "*.js" -o -name "*.css" | xargs ls -lh
"Identify bundle size and asset optimization improvements"

# Database performance
grep -r "SELECT\|findAll\|query" . --include="*.js" | head -20
"Analyze database query optimization points"

# Dependency performance impact
npm outdated && npm audit
"Evaluate performance impact of outdated dependencies"

Analysis Perspectives

1. Code-Level Problems

• O(n²) Algorithms: Detect inefficient array operations
• Synchronous I/O: Identify blocking processes
• Redundant Processing: Remove unnecessary calculations or requests
• Memory Leaks: Manage event listeners and timers

2. Architecture-Level Problems

• N+1 Queries: Database access patterns
• Missing Cache: Repeated calculations or API calls
• Bundle Size: Unnecessary libraries or code splitting
• Resource Management: Connection pools and thread usage

3. Technical Debt Impact

• Legacy Code: Performance degradation from old implementations
• Design Issues: High coupling from poor responsibility distribution
• Insufficient Testing: Missing performance regression detection
• Monitoring Gaps: Early problem detection system

Performance Improvement ROI Matrix

text
Improvement ROI = (Time Savings + Quality Improvement) ÷ Implementation Effort

| Priority | UX Impact | Implementation Difficulty | Time Savings | Example | Effort | Effect | | ------------------------------- | --------- | ------------------------- | ------------ | ------------------- | ------ | ------------- | | P0] Implement Now | High | Low | > 50% | CDN implementation | 8h | Response -60% | | P1] Early Implementation | High | Medium | 20-50% | Image optimization | 16h | Load -30% | | P2] Planned Implementation | Low | High | 10-20% | Code splitting | 40h | Initial -15% | | P3] Hold/Monitor | Low | Low | < 10% | Minor optimizations | 20h | Partial -5% |

Priority Criteria

• P0 (Immediate): High UX impact × Low difficulty = Maximum ROI
• P1 (Early): High UX impact × Medium difficulty = High ROI
• P2 (Planned): Low UX impact × High difficulty = Medium ROI
• P3 (Hold): Low UX impact × Low difficulty = Low ROI

Performance Metrics and UX Improvement Correlation

| Metric | Improvement | Perceived Speed | User Satisfaction | Implementation Effort | | -------------------------- | ----------- | --------------- | -------------------- | --------------------- | | LCP (Loading) | -0.5s | +30% | -7% bounce rate | 16h | | INP (Interaction) | -50ms | +15% | -20% stress | 8h | | CLS (Visual Stability) | -0.05 | +10% | -50% misclicks | 4h | | TTFB (Server) | -200ms | +25% | +40% perceived speed | 24h | | TTI (Interactive) | -1.0s | +35% | +15% completion rate | 32h | | Bundle Size | -30% | +20% | +25% first visit | 16h |

Measurement and Tools

Node.js / JavaScript

bash
# Profiling
node --prof app.js
clinic doctor -- node app.js

# Bundle analysis
npx webpack-bundle-analyzer
lighthouse --chrome-flags="--headless"

Database

sql
-- Query analysis
EXPLAIN ANALYZE SELECT ...
SHOW SLOW LOG;

Frontend

bash
# React performance
grep -r "useMemo\|useCallback" . --include="*.jsx"

# Resource analysis
find ./src -name "*.png" -o -name "*.jpg" | xargs ls -lh

Continuous Improvement

• Regular Audits: Run weekly performance tests
• Metrics Collection: Track response times and memory usage
• Alert Setup: Automatic notifications for threshold violations
• Team Sharing: Document improvement cases and anti-patterns