BMAD-METHOD/CURRENT-V2/docs/testing-strategy.md

Testing Strategy: WasaPrecruit MVP

This document outlines the testing strategy for the WasaPrecruit MVP to ensure quality, reliability, and correctness.

Goals

• Verify functional requirements are met.
• Ensure system stability and performance under expected load.
• Catch regressions before they reach production.
• Build confidence in deployments.
• Facilitate safe refactoring and modifications (by humans and AI).

Testing Levels

We will employ a multi-layered testing approach:

1. Static Analysis (Linting/Formatting):

   • Tools: ESLint, Prettier, TypeScript Compiler.
   • Scope: Enforce code style, detect syntax errors, enforce type safety.
   • Execution: Run automatically on commit hooks and in CI pipeline.
   • Rationale: Catches basic errors early and enforces consistency.

2. Unit Tests:

   • Tools: Jest or Vitest (for both Frontend and Backend Node.js/TS code).
   • Scope: Test individual functions, modules, components, and classes in isolation. Focus on business logic, utility functions, and pure UI components.
   • Execution: Run locally during development and in CI pipeline on every push/PR.
   • Mocking: Use Jest/Vitest mocking capabilities to isolate units from external dependencies (APIs, databases, cloud services).
   • Target Coverage: Aim for high coverage (>80%) of critical business logic.
   • Rationale: Fast feedback loop, verifies correctness of small units, enables safe refactoring.

3. Integration Tests:

   • Tools: Jest/Vitest, potentially with libraries like supertest (for HTTP endpoints) or tools to interact with deployed AWS resources (e.g., AWS SDK).
   • Scope: Test interactions between different components or services. Examples:
     • API endpoint handler correctly interacting with the database (using a test database or mocking the DB layer).
     • Message processing flow (e.g., WhatsApp Ingestor -> SQS -> Backend API Lambda).
     • Frontend component fetching data from the backend API (mocking the API).
   • Execution: Run in CI pipeline, potentially less frequently than unit tests due to longer execution time.
   • Rationale: Verifies collaboration between units and integration points.

4. End-to-End (E2E) Tests:

   • Tools: Playwright or Cypress.
   • Scope: Simulate real user scenarios by interacting with the live application (Frontend UI) through a browser. Examples:
     • Recruiter logs in, receives a message, views aspirant data, sends a reply.
     • Verify real-time message updates in the UI.
   • Environment: Run against a dedicated test/staging environment that mirrors production closely.
   • Execution: Run in CI pipeline, likely triggered less frequently (e.g., before production deployments) due to complexity and duration.
   • Rationale: Provides highest confidence that user flows work as expected across the entire stack.

5. Manual / Exploratory Testing:

   • Scope: Unscripted testing performed by humans to uncover usability issues, edge cases, or unexpected behavior not covered by automated tests.
   • Execution: Performed periodically, especially before major releases or after significant changes.
   • Rationale: Catches issues that automated tests might miss, provides qualitative feedback.

Testing Specific Areas

• Frontend (React UI):
  • Unit tests for components (logic & rendering, using React Testing Library).
  • Unit tests for hooks and state management stores.
  • Integration tests for data fetching.
  • E2E tests for user flows.
• Backend (Lambda Functions):
  • Unit tests for handlers and business logic (mocking AWS SDKs, DB interactions).
  • Integration tests for API endpoints/resolvers (using local mocks or testing against deployed dev/staging resources).
• AI Bot Logic:
  • Unit tests for the state machine/flow logic.
  • Integration tests verifying interaction with the WhatsApp sending mechanism.
• Infrastructure (IaC):
  • Linting and validation of CDK/Terraform code.
  • Testing deployed infrastructure (e.g., checking resource creation, basic connectivity) can be part of integration/E2E tests or specific infrastructure tests.

CI/CD Integration

• The CI/CD pipeline (e.g., GitHub Actions) will automate the execution of static analysis, unit tests, and integration tests on every pull request and push to main branches.
• E2E tests might run on merges to staging or before production deployment triggers.
• Builds/deployments should fail if tests do not pass.

Quality Gates

• Pull Requests: Require passing static analysis and unit/integration tests before merging.
• Staging Deployment: Require passing E2E tests before promoting to production.
• Code Coverage: Monitor code coverage trends, aiming for a baseline (e.g., 70-80% for unit tests on critical code) but focusing on testing quality over raw numbers.

Specialized Testing Types (Add sections as needed)

Performance Testing

• Scope & Goals: {What needs performance testing? What are the targets (latency, throughput)?}
• Tools: {e.g., K6, JMeter, Locust}

Security Testing

• Scope & Goals: {e.g., Dependency scanning, SAST, DAST, penetration testing requirements.}
• Tools: {e.g., Snyk, OWASP ZAP, Dependabot}

Accessibility Testing (UI)

• Scope & Goals: {Target WCAG level, key areas.}
• Tools: {e.g., Axe, Lighthouse, manual checks}

Visual Regression Testing (UI)

• Scope & Goals: {Prevent unintended visual changes.}
• Tools: {e.g., Percy, Applitools Eyes, Playwright visual comparisons}

Test Data Management

{How is test data generated, managed, and reset for different testing levels?}

Change Log

Change	Date	Version	Description	Author
Initial draft	YYYY-MM-DD	0.1	Initial draft	{Agent/Person}
...	...	...	...	...