tdd

name	tdd
description	Test-driven development with red-green-refactor loop. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, or asks for test-first development.

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 → refactor → 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→REFACTOR: test1→impl1→clean up
  RED→GREEN→REFACTOR: test2→impl2→clean up
  RED→GREEN→REFACTOR: test3→impl3→clean up
  ...

Workflow

0. Detect project language, conventions, and context

Before writing anything:

• Identify the project language and its idiomatic test patterns
• Identify the test framework already in use (or the standard one for the language)
• Identify the test command for the project (e.g., dotnet test, go test ./..., cargo test, npm test)
• Note existing test structure and naming conventions in the project
• Explore the codebase to understand existing modules, patterns, and similar features — so you don't duplicate or conflict with what's already there

Apply idiomatic patterns for the detected language:

• C#: xUnit/NUnit/MSTest. Use [Fact]/[Theory] (xUnit) or equivalent. Interfaces for DI. async Task for async tests.
• Go: Built-in testing package. Prefer table-driven tests with t.Run() subtests. Interfaces are implicit — test doubles just satisfy the interface. No mocking framework needed.
• Rust: Built-in #[test] in a #[cfg(test)] module. Use assert!/assert_eq!/assert_ne!. Traits + generics for DI. Integration tests go in tests/ directory. The compiler already catches many classes of bugs — focus tests on logic and behavior, not type safety.

Follow whatever conventions the project already uses. If the project has no tests yet, use the language's standard/most common framework.

1. Planning

Before writing any code:

• Confirm with user what interface changes are needed
• Confirm with user which behaviors to test (prioritize)
• Identify opportunities for deep modules (small interface, deep implementation)
• Design interfaces for testability
• List the behaviors to test (not implementation steps)
• Get user approval on the plan

Ask: "What should the public interface look like? Which behaviors are most important to test?"

You can't test everything. Confirm with the user exactly which behaviors matter most. Focus testing effort on critical paths and complex logic, not every possible edge case.

2. Tracer Bullet

Write ONE test that confirms ONE thing about the system:

RED:   Write test for first behavior → run tests → verify it FAILS
GREEN: Write minimal code to pass → run tests → verify it PASSES
REFACTOR: Clean up while green → run tests → verify still green

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

Always run the test command to verify each state transition. Do not assume — confirm.

3. Incremental Loop

For each remaining behavior:

RED:     Write next test → run tests → verify it FAILS
GREEN:   Minimal code to pass → run tests → verify it PASSES
REFACTOR: Clean up if needed → run tests → verify still green

Rules:

• One test at a time
• Only enough code to pass current test
• Don't anticipate future tests
• Keep tests focused on observable behavior
• Refactor after each GREEN, not only at the end

4. Handling unexpected results

**Test passes when it should fail (RED fails):** The behavior already exists, or the test is wrong. Investigate: - If the behavior already exists, the test is validating existing code — that's useful, but don't write new implementation. Move on to the next behavior. - If the test is wrong (not actually testing what you intended), fix the test until it properly fails for the right reason. **Test still fails after implementation (GREEN fails):** - Read the failure message carefully — it often points directly to the issue. - Check whether the test is asserting on the right thing (did the interface change during implementation?). - Check whether the implementation is wired up correctly (is the test reaching the new code?). - If the fix isn't obvious, narrow the problem: does the implementation work in isolation? Is it a test setup issue? - Do not modify the test to make it pass unless the test itself is wrong. The test defines the behavior — the implementation must satisfy it.

5. Final Review

After all behaviors are implemented, do a final review pass for refactor candidates:

• Look across all new code for duplication that only became visible after multiple cycles
• Deepen modules (move complexity behind simple interfaces)
• Consider what the 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
[ ] Tests actually run and confirm RED then GREEN
[ ] Code is minimal for this test
[ ] No speculative features added
[ ] Refactored while green (if needed)