How Cocode verifies AI-assisted features

Turn requirements into observable outcomes

A feature needs concrete completion criteria. A visible screen and a working button do not establish how it behaves with invalid input or a failed save.

“Users can save files” leaves questions open: what happens without write permission, and how are unsaved changes shown? Answering these questions defines both the implementation and its checks. Cocode carries those criteria into unit tests and BDD integration tests.

Unit tests check individual rules

Unit tests supply inputs to a small piece of behavior and check its output. This makes failures easier to locate in rules such as state mapping or error handling.

Cocode tests how modified, added and deleted files map to change badges, and checks that unavailable Git status produces no change badges. Keeping both normal and exceptional cases makes these rules repeatable checks after implementation changes.

BDD integration tests connect actions to outcomes

Individually correct functions can still fail when screens, state handling and file operations interact. BDD (behavior-driven development) integration tests describe a situation, an action and an expected outcome, then execute that scenario in the app.

A Cocode save-failure scenario specifies:

• Given an edited file whose disk copy is read-only.
• When the user saves it.
• Then a save-failure notice appears and the file remains marked as having unsaved changes.

The scenario gives planners and developers a shared description of the expected behavior, with criteria that remain useful as the implementation changes.

Recheck existing behavior after changes

New features and shared-code changes can affect existing behavior. Rerunning unit tests and BDD integration tests checks for changed outcomes in the rules and flows they cover. This is regression testing.

The value lies in what the tests check: which requirements they cover, whether they include failures, and which flows a change affects. Cocode combines both levels so a feature comes with checks that can be used again.

People review the criteria and coverage

When AI writes both code and tests, it can carry the same misunderstanding into both. Engineers compare expected outcomes with agreed requirements and review missing failure cases. A passing result must be read alongside what was checked.

People also assess clarity and usability. An engineer makes the release decision using both test results and that review. Cocode connects concrete requirements, unit tests, BDD integration tests and human review to keep quality assessable as features evolve.