Introduction
When building software, different parts need to work together smoothly. Problems often happen not inside a single part, but when these parts connect. Integration testing helps find issues in how these parts interact.
Imagine a team building a car where each person assembles different parts like the engine, wheels, and electronics. Even if each part works well alone, the car only runs smoothly when all parts fit and work together perfectly.
┌───────────────┐ ┌───────────────┐ ┌───────────────┐
│ Module A │────▶│ Module B │────▶│ Module C │
└───────────────┘ └───────────────┘ └───────────────┘
│ │ │
▼ ▼ ▼
Unit Tests Integration Testing System Testingimport unittest # Example modules class ModuleA: def get_data(self): return 'data from A' class ModuleB: def process(self, input_data): return input_data.upper() class IntegrationTest(unittest.TestCase): def test_modules_integration(self): a = ModuleA() b = ModuleB() data = a.get_data() result = b.process(data) self.assertEqual(result, 'DATA FROM A') if __name__ == '__main__': unittest.main()
integration testing in software development?ModuleA returns a number, and ModuleB doubles that number. Which integration test output is correct if ModuleA returns 5?Auth, Profile, and Notifications. Auth sends user info to Profile, which then triggers Notifications. Which integration test scenario best checks the full flow?Auth sending data to Profile, then Profile triggering Notifications. Testing this chain checks integration.Auth sending data to Profile and Profile triggering Notifications tests the full flow of data and triggers across all three modules together.Pass the test and this pattern moves unknown