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Architecture Documentation

This section contains comprehensive technical architecture documentation for the Remind Tools monorepo.

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Architecture Overview

Remind Tools follows a Clean Architecture + Domain-Driven Design (DDD) approach, ensuring:
  • Separation of concerns
  • Testability and maintainability
  • Scalability across multiple platforms
  • Code reusability through shared packages

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Documentation Structure

System Design

High-level system architecture and component interactions

Decision Records

Architectural Decision Records (ADRs) documenting key choices

Technical Specifications

Detailed technical specifications for features and components

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Technology Stack

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Frontend

  • Flutter: Cross-platform framework (iOS, Android, Web, Desktop)
  • State Management: BLoC + Riverpod hybrid approach
  • UI Components: Material Design 3 with custom theming

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Backend

  • Supabase: PostgreSQL database with real-time capabilities
  • Authentication: Supabase Auth with social providers
  • Edge Functions: Serverless compute for business logic

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Integrations

  • AI: Google Gemini Pro for intelligent features
  • Maps: MapBox GL for 3D mapping and navigation
  • Analytics: Custom event tracking and monitoring

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Architectural Principles

  1. Clean Architecture Layers
    • Presentation Layer (UI/Controllers)
    • Domain Layer (Business Logic/Entities)
    • Data Layer (Repositories/Data Sources)
  2. Domain-Driven Design
    • Bounded contexts for each application
    • Rich domain models
    • Ubiquitous language
  3. SOLID Principles
    • Single Responsibility
    • Open/Closed
    • Liskov Substitution
    • Interface Segregation
    • Dependency Inversion

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Monorepo Structure

remind_tools/
├── apps/           # Flutter applications
│   ├── trips_app/  # Travel planning app
│   └── money_app/  # Finance management app
├── packages/       # Shared packages
│   ├── core/       # Core utilities
│   ├── domain/     # Domain models
│   ├── data/       # Data layer
│   └── ui/         # Shared UI components

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Performance Considerations

  • Lazy loading and code splitting
  • Optimized asset management
  • Efficient state management
  • Database query optimization
  • Caching strategies