4. Performance & Optimization

Performance Metrics

Code Minification Enabled100 / 100
Resource Shrinking Enabled100 / 100
Asset Optimization30 / 100
Memory Management60 / 100

4.1 App Size & Bundle Analysis

Status: ✅Pass

Findings:

  • Code obfuscation enabled: minifyEnabled = true and shrinkResources = true in release builds - good for app size
  • ProGuard/R8 enabled: ProGuard rules configured and active in release builds
  • Unoptimized assets: Images stored as PNG/JPEG without compression optimization
  • No asset optimization: No evidence of image compression, WebP conversion, or asset optimization
  • Multiple image resolutions: Images provided in 1.0x, 2.0x, 3.0x resolutions (good practice) but files may not be optimized

Evidence:

  • android/app/build.gradle lines 99-104: minifyEnabled true and shrinkResources true in release builds
  • android/app/proguard-rules.pro: ProGuard rules configured and used
  • pubspec.yaml assets section (lines 129-147): Images listed without optimization
  • Assets directory contains PNG/JPEG files: background.png, logo-normal.png, logo-wide.png, logo-super-wide.png, action-logo.png, camerascope.png, icon.jpg, header.jpg, pump.png, marker40.png
  • Multiple resolution folders: 1.0x/, 2.0x/, 3.0x/ for location images (good practice)
  • No WebP conversion or image compression tools in use

Risk Level: Low Risk

Recommendation:

  • Immediate actions:
  • Analyze bundle size using flutter build appbundle --analyze-size or flutter build apk --analyze-size
  • Optimize images (compress PNGs, convert to WebP where appropriate)
  • Remove unused assets and resources
  • Short-term:
  • Use image optimization tools (e.g., flutter_image_compress)
  • Review and remove unused dependencies
  • Consider lazy loading for large assets

4.2 Memory Management

Status: ⚠️Warning

Findings:

  • Image memory usage: Image.memory() used for loading images from bytes without size limits or caching strategy
  • Some dispose methods implemented: Some routes properly implement dispose() (e.g., dashboard_route.dart, camera_route.dart, video_route.dart, launch_route.dart)
  • Timer usage: Timer properly cancelled in count_down_timer_widget.dart (good example)
  • No memory leak detection: No evidence of memory profiling or leak detection tools
  • Large image loading: Images loaded into memory as Uint8List without size validation
  • State persistence: State saved to database on every change, potential performance impact
  • Connectivity state: Connectivity state managed but no stream subscription found (unlike Tinq4U)

Evidence:

  • lib/widgets/supertank_action_app_decoration.dart: Image.memory() usage (line 50)
  • lib/widgets/navigation_drawer.dart: Image.memory() usage (line 65)
  • lib/widgets/fixed_floating_button_widget.dart: Image.memory() usage (line 65)
  • lib/widgets/count_down_timer_widget.dart: Image.memory() usage (line 291)
  • lib/widgets/action_slide_widget.dart: Image.memory() usage (line 147)
  • lib/widgets/count_down_timer_widget.dart: Timer properly cancelled in dispose (line 28) - good example
  • lib/routes/dashboard_route.dart: Proper dispose implementation (lines 63-66)
  • lib/routes/camera_route.dart: Proper dispose implementation (lines 53-55)
  • lib/routes/video_route.dart: Proper dispose implementation (lines 43-48)
  • lib/routes/launch_route.dart: Proper dispose implementation (lines 116-122)
  • lib/states/session_state.dart: State saved to database on every setter call (lines 58-97) - potential performance issue

Risk Level: Medium Risk

Recommendation:

  • Immediate actions:
  • Add memory limits for image loading (validate image size before loading)
  • Implement proper image caching strategy
  • Review all dispose methods for completeness
  • Short-term:
  • Add memory profiling to identify leaks
  • Implement image size validation before loading
  • Use image caching library (e.g., cached_network_image for network images)
  • Optimize database write operations (batch updates instead of per-change writes)
  • Consider using Image.asset() instead of Image.memory() where possible

4.3 Network Performance

Status: ⚠️Warning

Findings:

  • Firebase Performance monitoring implemented: Performance traces added to routes and Dio interceptor for network monitoring
  • Timeout configuration: Network timeouts set to 30 seconds (longer than typical 20 seconds, may be too long for some operations)
  • No request caching: No evidence of HTTP response caching or request deduplication
  • No request batching: Multiple individual API calls instead of batched requests where possible
  • Token refresh creates new Dio instance: Token refresh creates separate Dio client, potential overhead
  • No request retry logic: No automatic retry mechanism for failed network requests
  • Firebase Performance interceptor: Dio interceptor properly configured for performance monitoring

Evidence:

  • lib/singletons/dio_singleton.dart lines 25-26: Timeout configuration (30 seconds for connect and receive)
  • lib/singletons/dio_singleton.dart lines 28-30: Firebase Performance interceptor added to Dio
  • lib/singletons/dio_singleton.dart lines 62-63: New Dio instance created for token refresh (overhead)
  • Multiple routes with Firebase Performance tracing:
    • lib/routes/login_route.dart (lines 47-52)
    • lib/routes/generic_route.dart (lines 29-34)
    • lib/routes/webview_route.dart (lines 37-42)
    • And 30+ more routes with similar tracing
  • No HTTP cache implementation found
  • No request batching or queuing mechanism
  • No retry logic in error handlers

Risk Level: Medium Risk

Recommendation:

  • Immediate actions:
  • Consider reducing timeout from 30 seconds to 20 seconds for better user experience
  • Implement HTTP response caching for static/rarely-changing data
  • Add request retry logic for transient failures
  • Optimize token refresh to reuse existing Dio instance where possible
  • Short-term:
  • Implement request deduplication for identical concurrent requests
  • Add request prioritization for critical operations
  • Batch related API calls where possible
  • Review Firebase Performance traces to identify slow endpoints

4.4 Battery & Resource Usage

Status: ✅Pass

Findings:

  • Location services: OneSignal location sharing disabled (OneSignal.Location.setShared(false)) - good for battery
  • Connectivity monitoring: Connectivity state managed without continuous stream subscription (better than Tinq4U)
  • Camera usage: Camera resources properly disposed in camera_route.dart
  • Firebase services: Multiple Firebase services initialized but properly configured

Evidence:

  • lib/main_prod.dart line 32: OneSignal.Location.setShared(false) - location sharing disabled (good)
  • lib/main_staging.dart line 32: OneSignal.Location.setShared(false) - location sharing disabled (good)
  • lib/states/connectivity_state.dart: Simple state management without continuous stream subscription
  • lib/routes/camera_route.dart: Camera properly disposed (lines 53-55, 163)
  • lib/main_prod.dart lines 24, 36-37: Firebase services initialized (Core, Crashlytics, Performance, Analytics, Remote Config)

Risk Level: Low Risk

Recommendation:

  • Immediate actions:
  • Continue monitoring battery usage in production
  • Short-term:
  • Review Firebase service usage and disable unused services if any
  • Implement efficient push notification handling
  • Monitor location service usage patterns