Testing Strategy Builder

Overview

This skill provides comprehensive guidance for building effective testing strategies that ensure software quality, reliability, and maintainability. Whether starting from scratch or improving existing test coverage, this framework helps teams design robust testing approaches.

When to use this skill:

• Planning testing strategy for new projects or features
• Improving test coverage in existing codebases
• Establishing quality gates and coverage targets
• Designing test automation architecture
• Creating test plans and test cases
• Choosing appropriate testing tools and frameworks
• Implementing continuous testing in CI/CD pipelines

Bundled Resources:

• references/code-examples.md - Detailed testing code examples
• templates/test-plan-template.md - Comprehensive test plan template
• templates/test-case-template.md - Test case documentation template
• checklists/test-coverage-checklist.md - Coverage verification checklist

Required Tools

This skill references the following testing tools. Not all are required - the skill will recommend appropriate tools based on your project.

JavaScript/TypeScript Testing

• Jest: Most popular testing framework

  • Install: npm install --save-dev jest @types/jest
  • Config: npx jest --init

• Vitest: Vite-native testing framework

  • Install: npm install --save-dev vitest
  • Config: Add to vite.config.ts

• Playwright: End-to-end testing

  • Install: npm install --save-dev @playwright/test
  • Setup: npx playwright install

• k6: Performance testing

  • Install (macOS): brew install k6
  • Install (Linux): Download from k6.io
  • Command: k6 run script.js

Python Testing

• pytest: Standard Python testing framework

  • Install: pip install pytest
  • Command: pytest

• pytest-cov: Coverage reporting

  • Install: pip install pytest-cov
  • Command: pytest --cov=.

• Locust: Performance testing

  • Install: pip install locust
  • Command: locust -f locustfile.py

Coverage Tools

• c8: JavaScript/TypeScript coverage

  • Install: npm install --save-dev c8
  • Command: c8 npm test

• Istanbul/nyc: Alternative JS coverage

  • Install: npm install --save-dev nyc
  • Command: nyc npm test

Installation Verification

# JavaScript/TypeScript
jest --version
vitest --version
playwright --version
k6 version

# Python
pytest --version
locust --version

# Coverage
c8 --version
nyc --version

Note: The skill will guide you to select tools based on your project framework (React, Vue, FastAPI, Django, etc.) and testing needs.

Testing Philosophy

The Testing Trophy 🏆

Modern testing follows the "Testing Trophy" model (evolved from the testing pyramid):

         🏆
       /    \
      /  E2E  \         ← Few (critical user journeys)
     /----------\
    / Integration\      ← Many (component interactions)
   /--------------\
  /     Unit       \    ← Most (business logic)
 /------------------\
/  Static Analysis   \  ← Foundation (linting, type checking)

Principles:

1. Static Analysis: Catch syntax errors, type issues, and common bugs before runtime
2. Unit Tests: Test individual functions and components in isolation
3. Integration Tests: Test how components work together
4. E2E Tests: Validate critical user workflows end-to-end

Balance: 70% integration, 20% unit, 10% E2E (adjust based on context)

Testing Strategy Framework

1. Coverage Targets

Recommended Targets:

• Overall Code Coverage: 80% minimum
• Critical Paths: 95-100% (payment, auth, data mutations)
• New Features: 100% coverage requirement
• Business Logic: 90%+ coverage
• UI Components: 70%+ coverage

Coverage Types:

• Line Coverage: Percentage of code lines executed
• Branch Coverage: Percentage of decision branches taken
• Function Coverage: Percentage of functions called
• Statement Coverage: Percentage of statements executed

Important: Coverage is a metric, not a goal. 100% coverage ≠ bug-free code.

2. Test Classification

Static Analysis

Purpose: Catch errors before runtime Tools: ESLint, Prettier, TypeScript, Pylint, mypy, Ruff When to run: Pre-commit hooks, CI pipeline

Unit Tests

Purpose: Test isolated business logic Tools: Jest, Vitest, pytest, JUnit Characteristics:

• Fast execution (< 100ms per test)
• No external dependencies (database, API, filesystem)
• Deterministic (same input = same output)
• Test single responsibility

Coverage Target: 90%+ for business logic

See references/code-examples.md for detailed unit test examples.

Integration Tests

Purpose: Test component interactions Tools: Testing Library, Supertest, pytest with fixtures Characteristics:

• Test multiple units working together
• May use test databases or mocked external services
• Moderate execution time (< 1s per test)
• Focus on interfaces and contracts

Coverage Target: 70%+ for API endpoints and component interactions

See references/code-examples.md for API integration test examples.

End-to-End (E2E) Tests

Purpose: Validate critical user journeys Tools: Playwright, Cypress, Selenium Characteristics:

• Test entire application flow (frontend + backend + database)
• Slow execution (5-30s per test)
• Run against production-like environment
• Focus on business-critical paths

Coverage Target: 5-10 critical user journeys

See references/code-examples.md for complete E2E test examples.

Performance Tests

Purpose: Validate system performance under load Tools: k6, Artillery, JMeter, Locust Types:

• Load Testing: System behavior under expected load
• Stress Testing: Breaking point identification
• Spike Testing: Sudden traffic surge handling
• Soak Testing: Sustained load over time (memory leaks)

Coverage Target: Test all performance-critical endpoints

See references/code-examples.md for k6 load test examples.

Test Planning

1. Risk-Based Testing

Prioritize testing based on risk assessment:

High Risk (100% coverage required):

• Payment processing
• Authentication and authorization
• Data mutations (create, update, delete)
• Security-critical operations
• Compliance-related features

Medium Risk (80% coverage):

• Business logic
• Data transformations
• API integrations
• Email/notification systems

Low Risk (50% coverage):

• UI styling
• Static content
• Read-only operations
• Non-critical features

2. Test Case Design

Given-When-Then Pattern:

Given [initial context]
When [action occurs]
Then [expected outcome]

This pattern keeps tests clear and focused. See references/code-examples.md for implementation examples.

3. Test Data Management

Strategies:

• Fixtures: Pre-defined test data in JSON/YAML files
• Factories: Generate test data programmatically
• Seeders: Populate test database with known data
• Faker Libraries: Generate realistic random data

See references/code-examples.md for test factory and fixture examples.

Testing Patterns and Best Practices

1. AAA Pattern (Arrange-Act-Assert)

Structure tests in three clear phases:

• Arrange: Set up test data and context
• Act: Perform the action being tested
• Assert: Verify expected outcomes

See references/code-examples.md for detailed AAA pattern examples.

2. Test Isolation

Each test should be independent:

• Use fresh test database for each test
• Clean up resources after each test
• Tests don't depend on execution order

See references/code-examples.md for test isolation patterns.

3. Mocking vs Real Dependencies

When to Mock:

• External APIs (payment gateways, third-party services)
• Slow operations (file I/O, network calls)
• Non-deterministic behavior (curre