Philosophy
Core principle: Tests should verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't.
Good tests are integration-style: they exercise real code paths through public APIs. They describe what the system does, not how it does it. A good test reads like a specification - "user can checkout with valid cart" tells you exactly what capability exists. These tests survive refactors because they don't care about internal structure.
Bad tests assert incidental implementation rather than the contract. Prefer public behavior; direct database or filesystem checks are appropriate when persistence, constraints, migrations, or external effects are the contract. The warning sign is a test changing solely because a private function was renamed while observable behavior stayed the same.
See tests.md for examples and mocking.md for mocking guidelines.
Anti-Pattern: Horizontal Slices
DO NOT write all tests first, then all implementation. This is "horizontal slicing" - treating RED as "write all tests" and GREEN as "write all code."
This produces crap tests:
- Tests written in bulk test imagined behavior, not actual behavior
- You end up testing the shape of things (data structures, function signatures) rather than user-facing behavior
- Tests become insensitive to real changes - they pass when behavior breaks, fail when behavior is fine
- You outrun your headlights, committing to test structure before understanding the implementation
Correct approach: Vertical slices via tracer bullets. One test → one implementation → repeat. Each test responds to what you learned from the previous cycle. Because you just wrote the code, you know exactly what behavior matters and how to verify it.
WRONG (horizontal):
RED: test1, test2, test3, test4, test5
GREEN: impl1, impl2, impl3, impl4, impl5
RIGHT (vertical):
RED→GREEN: test1→impl1
RED→GREEN: test2→impl2
RED→GREEN: test3→impl3
...
Workflow
1. Planning
Before writing any code:
- Infer the requested interface and priority behaviors from the user's specification and existing code
- Identify opportunities for deep modules (small interface, deep implementation)
- Design interfaces for testability
- List the behaviors to test (not implementation steps)
- Ask only when a missing choice materially changes the public interface or behavior
If the request already specifies the interface and behavior, start the first red-green cycle without re-asking. Focus testing effort on critical paths and complex logic rather than mirroring every implementation detail.
2. Tracer Bullet
Write ONE test that confirms ONE thing about the system:
RED: Write test for first behavior → test fails
GREEN: Write minimal code to pass → test passes
This is the first verified path through the selected test boundary. Call it end-to-end only if the test actually exercises the complete runtime flow. Confirm RED fails for the intended missing behavior, not a syntax, import, environment, or setup error.
3. Incremental Loop
For each remaining behavior:
RED: Write next test → fails
GREEN: Minimal code to pass → passes
Rules:
- One test at a time
- Only enough code to pass current test
- Don't anticipate future tests
- Keep tests focused on observable behavior
4. Refactor
After all tests pass, look for refactor candidates:
- Extract duplication where it represents the same responsibility
- Deepen modules (move complexity behind simple interfaces)
- Apply SOLID principles where natural
- Consider what new code reveals about existing code
- Run tests after each refactor step
Never refactor while RED. Get to GREEN first.
Checklist Per Cycle
[ ] Test describes behavior, not implementation
[ ] Test uses public interface only
[ ] Test would survive internal refactor
[ ] Code is minimal for this test
[ ] No speculative features added