🧪 Integration and Load Testing

🔗 Integration Testing

Integration testing ensures that different modules or services in a system work together as expected. It is typically performed after unit testing and before system testing.

✅ Purpose

• Validate data flow between modules
• Detect interface mismatches and contract violations
• Ensure modules integrate correctly in real-world scenarios

🧪 Types

• Big Bang Integration: All components are integrated at once and tested together
• Incremental Integration: Modules are integrated and tested step-by-step
  • Top-down: Start from top-level modules
  • Bottom-up: Start from lower-level modules
  • Sandwich: Mix of top-down and bottom-up

🛠️ Tools

• NUnit, xUnit (for .NET)
• JUnit (for Java)
• TestNG, Postman (for API integration)

✅ Best Practices

• Use mocks/stubs for unavailable modules
• Automate integration tests for CI/CD
• Test both happy and edge cases
• Keep tests isolated and repeatable

⚙️ Load Testing

Load testing evaluates how a system performs under expected and peak user loads. It helps identify performance bottlenecks and ensures scalability.

✅ Purpose

• Measure system responsiveness and stability
• Identify performance bottlenecks
• Ensure system can handle expected traffic

🧪 Types

• Baseline Load Testing: Normal expected usage
• Stress Testing: Beyond maximum capacity
• Spike Testing: Sudden increase in load
• Soak Testing: Sustained load over time

🛠️ Tools

• Apache JMeter
• Locust
• k6
• LoadRunner
• Azure Load Testing

✅ Best Practices

• Simulate real-world user behavior
• Test early and often
• Monitor CPU, memory, and response times
• Use dashboards for real-time insights

📚 Summary

• Integration Testing ensures modules work together correctly
• Load Testing ensures system performance under stress
• Both are essential for delivering robust, scalable applications