Grade My Investments Technology Observatory
GMI · TECHNOLOGY OBSERVATORY // ALL SYSTEMS NOMINAL
ENGINEERED BY LEOPARD DATA

Testable Architecture of Grade My Investments

Comprehensive testing strategy with 695 unit and integration tests ensuring robust, reliable, and maintainable code.

Testing Philosophy

The Grade My Investments platform is built with testability as a core architectural principle. Every component, service, and integration point is designed to be testable in isolation, enabling rapid development cycles, confident refactoring, and reliable deployments.

Our comprehensive test suite of 695 tests (583 unit + 95 integration + 17 engine) covers critical business logic, data access patterns, API endpoints, authentication, authorization, and integration points, ensuring system reliability and facilitating continuous delivery.

TEST LAYERS
rendering diagram…
flowchart TB
    subgraph UNIT[Gmi.UnitTests - 583 tests]
        U1[Services - 335]:::svc
        U2[Repositories - 145]:::svc
        U3[Azure Functions - 116]:::svc
    end
    subgraph INT[Gmi.DataAccess.IntegrationTests - 95 tests]
        I1[EF Core - Repositories]:::data
        I2[CRUD Operations]:::data
    end
    subgraph ENG[Gmi.ReportEngine.Tests - 17 tests]
        E1[Financial Calculations]:::svc
        E2[Report Accuracy]:::svc
    end
    subgraph TOOLS[Test Tools]
        T1([xUnit]):::ext
        T2([Moq]):::ext
        T3([FluentAssertions]):::ext
        T4([EF InMemory]):::ext
    end
    subgraph CICD[CI - CD Gate]
        P[Azure DevOps Pipeline]:::sec
        Q{All Pass?}:::sec
    end
    UNIT --> P
    INT --> P
    ENG --> P
    P --> Q
    Q -->|yes| R([Deploy]):::app
    Q -->|no| S([Block Deploy]):::app
    TOOLS -.->|power| UNIT
    TOOLS -.->|power| INT
classDef app fill:#1f2630,stroke:#C0894E,color:#F3EFE8;
classDef svc fill:#241c14,stroke:#E2B583,color:#F3EFE8;
classDef data fill:#22201a,stroke:#C0894E,color:#EBD3AE;
classDef ext fill:#1b1f27,stroke:#5A616B,color:#C4C0B8;
classDef sec fill:#1d2733,stroke:#5cc8e0,color:#eafaff;
695 tests span three projects covering services, repositories, Azure Functions, and the report engine.

Test Project Structure

Test Project Target Components Test Count Coverage Focus
Gmi.UnitTests Services, API functions, repositories 583 tests Business rules, data validation, API contracts
Gmi.DataAccess.IntegrationTests Entity Framework, repositories, database operations 95 tests Data access patterns, CRUD operations
Gmi.ReportEngine.Tests Report generation engine, calculations 17 tests Financial calculations, report accuracy

Testing Patterns & Practices

Dependency Injection
  • • Services designed for DI container
  • • Interface-based abstractions
  • • Easy mocking and stubbing
  • • Isolated unit testing
Repository Pattern
  • • Abstracted data access
  • • In-memory test repositories
  • • Database-independent tests
  • • Fast test execution
Service Layer Testing
  • • Business logic isolation
  • • Mocked external dependencies
  • • End-to-end scenario testing
  • • Error handling validation
Calculation Engine Testing
  • • Mathematical precision validation
  • • Edge case boundary testing
  • • Performance benchmarking
  • • Historical data accuracy

Test Categories & Coverage

Unit Tests
  • Services (335 tests) 335 tests
  • Repositories (145 tests) 145 tests
  • Azure Functions (116 tests) 116 tests
Integration & Engine Tests
  • Database Integration (95 tests) 95 tests
  • Report Engine (17 tests) 17 tests

Testing Tools & Frameworks

xUnit

Primary testing framework for .NET projects

Moq

Mocking framework for dependencies and external services

FluentAssertions

Readable and expressive test assertions

Entity Framework InMemory

In-memory database for fast data access testing

BenchmarkDotNet

Performance testing and benchmarking

Coverlet

Code coverage analysis and reporting

Test Metrics
  • Total Tests: 695 tests
  • Code Coverage: 89%
  • Pass Rate: 99.8%
  • Execution Time: < 3 minutes
  • Critical Path Coverage: 100%
  • Business Logic Coverage: 95%
Testing Benefits
  • Rapid development cycles
  • Confident refactoring
  • Early bug detection
  • Regression prevention
  • Documentation via tests
  • Deployment confidence
CI/CD Integration

All tests run automatically on every pull request and deployment, ensuring code quality gates are maintained.

  • Pre-commit hooks
  • PR validation
  • Azure DevOps pipeline
  • Quality gates
Focus Areas
Financial Calculations 100%
Data Access Layer 95%
Business Logic 92%
Integration Points 85%