tdd

Test-Driven Development

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 are coupled to implementation. They mock internal collaborators, test private methods, or verify through external means (like querying a database directly instead of using the interface). The warning sign: your test breaks when you refactor, but behavior hasn't changed. If you rename an internal function and tests fail, those tests were testing implementation, not behavior.

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:

• Confirm what interface changes are needed, using aligning-requirements context if already covered
• Confirm which behaviors to test when priorities are ambiguous
• Identify opportunities for deep modules (small interface, deep implementation)
• Design interfaces for testability
• List the behaviors to test (not implementation steps)
• Get user approval only when the test plan changes scope or exposes a meaningful product decision

Answer from the request and repo context first:

• What should the public interface look like?
• Which behaviors are most important to test?

Ask the user only when the answer would change implementation direction or product behavior. If the request and surrounding code already pin both down, do not stop to ask — that is the DevConcept philosophy applied to TDD: not ceremonial by default, but rigorous when the risk justifies it.

You can't test everything. Focus testing effort on critical paths and complex logic, not every possible edge case. Confirm priorities with the user only when the trade-off changes scope or product behavior.

Before editing production code, state the first behavior test you will make fail and the command you expect to run. If no practical behavior test exists, state that before coding and treat later checks as verification rather than TDD.

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 your tracer bullet - proves the path works end-to-end.

The RED step must be observable in the session: run the narrow test command and record the failing command/result before editing implementation. A test added after the implementation is useful verification, but it does not count as TDD and must be reported as test-after.

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
• 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
[ ] RED evidence was observed before implementation, or TDD was explicitly marked impractical
[ ] Test would survive internal refactor
[ ] Code is minimal for this test
[ ] No speculative features added

Expected Output

Behavior under test:
RED:
- test/command/result
GREEN:
- change made
- test/command/result
Refactor:
- done | skipped + reason