Happy path

The primary, expected flow through a feature or user journey, where all inputs are valid and everything works as intended. Testing the happy path confirms that the core functionality works under normal conditions, but it represents only a fraction of the scenarios a tester should cover. A skilled tester uses the happy path as a baseline and then designs additional tests for invalid inputs, edge cases, boundary conditions, and failure states. AI tools can help extend coverage beyond the happy path quickly, but they depend on the tester having already understood the happy path before evaluating what the AI produces.

Definition: The primary expected flow through a feature where valid inputs produce the intended result. A happy path also includes the things a system should not do under normal conditions, so legitimate "shouldn't" behaviours belong to the happy path rather than being treated as edge cases.

So what? Treating "shouldn't" behaviours as part of normal operation, rather than as afterthoughts, widens what counts as the expected path and reduces the chance of leaving constraints untested.

Example: A user with the wrong permissions not seeing a restricted menu option is part of the happy path, not an exceptional case.