test-driven-development

Test-Driven Development (TDD)

Overview

Write the test first. Watch it fail. Write minimal code to pass.

Core principle: If you didn't watch the test fail, you don't know if it tests the right thing.

Violating the letter of the rules is violating the spirit of the rules.

The Iron Law

NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST

Write code before the test? Delete it. Start over.

No exceptions:

• Don't keep it as "reference"
• Don't "adapt" it while writing tests
• Don't look at it
• Delete means delete

Implement fresh from tests. Period.

Outside-In Development

Start every feature with a high-level test that describes behavior from the user's perspective. Let each failure guide what to build next. Drop to unit tests when you encounter non-trivial logic.

Read examples/outside-in-testing.md for a complete walkthrough and examples/testing-pyramid.md for how test types combine into an optimal suite.

The Outer Loop: Feature Specs

1. Take the user story
2. Write a feature spec describing the behavior end-to-end
3. Run it — watch it fail
4. The error tells you what to build next: a route, a controller action, a view, a model method
5. Build the minimum to get past that error
6. Run again — next error drives next piece
7. When you hit non-trivial logic, drop to the inner loop

Feature specs use real database records. No mocks — except for external services (use webmock or fakes). Tests should run without an internet connection.

The Inner Loop: Unit Tests

When the feature spec error points to logic that needs its own proof — a search method, a calculation, a validation rule:

1. Write a unit test for that specific behavior
2. Follow Red-Green-Refactor (below)
3. Pass the unit test
4. Return to the feature spec — next error drives next piece

Unit tests isolate the object under test. Mock collaborators aggressively — the goal is to prove the functionality of this object, not its collaborators. Difficulty testing two objects in isolation signals too-tight coupling.

When to Drop Down

Not every piece needs a unit test. The feature spec covers the glue.

Just build it (feature spec covers it):

• Routes
• Empty controller actions
• Simple views and partials
• Wiring and delegation

Unit test first (non-trivial logic):

• Model methods with business logic
• Service objects
• Query objects
• Calculations, validations, transformations

The testing pyramid: many unit tests at the bottom, few feature tests at the top. Unit tests are fast and precise. Feature tests prove the system works end-to-end. Each plays to its strengths.

Red-Green-Refactor

The inner cycle. Every unit test follows this loop — and so does each error-driven step in the outer loop.

digraph tdd_cycle {
    rankdir=LR;
    red [label="RED\nWrite failing test", shape=box, style=filled, fillcolor="#ffcccc"];
    verify_red [label="Verify fails\ncorrectly", shape=diamond];
    green [label="GREEN\nMinimal code", shape=box, style=filled, fillcolor="#ccffcc"];
    verify_green [label="Verify passes\nAll green", shape=diamond];
    refactor [label="REFACTOR\nClean up", shape=box, style=filled, fillcolor="#ccccff"];
    next [label="Next", shape=ellipse];

    red -> verify_red;
    verify_red -> green [label="yes"];
    verify_red -> red [label="wrong\nfailure"];
    green -> verify_green;
    verify_green -> refactor [label="yes"];
    verify_green -> green [label="no"];
    refactor -> verify_green [label="stay\ngreen"];
    verify_green -> next;
    next -> red;
}

RED — Write Failing Test

Write one minimal test showing what should happen.

<Good>

RSpec.describe Item, ".search" do
  it "filters items by the search term" do
    desired_item = create(:item, name: "Widget")
    _other_item = create(:item, name: "Gadget")

    expect(Item.search("Widget")).to eq [desired_item]
  end
end

Clear name, tests real behavior, one thing.

</Good>

<Bad>

it "search works" do
  relation = spy("relation")
  allow(Item).to receive(:where).and_return(relation)

  Item.search("Widget")

  expect(Item).to have_received(:where).with(name: "Widget")
end

Vague name, tests spy interactions not real behavior, proves nothing about whether search actually returns the right items.

</Bad>

Requirements:

• One behavior
• Clear name
• Feature specs: real records, no mocks (except external services)
• Unit tests: mock collaborators, test the object in isolation

Verify RED — Watch It Fail

MANDATORY. Never skip.

bundle exec rspec spec/models/item_spec.rb

Confirm:

• Test fails (not errors)
• Failure message is expected
• Fails because feature missing (not typos)

Test passes? You're testing existing behavior. Fix test.

Test errors? Fix error, re-run until it fails correctly.

GREEN — Minimal Code

Write simplest code to pass the test.

<Good>

class Item < ApplicationRecord
  def self.search(term)
    where(name: term)
  end
end

Just enough to pass.

</Good>

<Bad>

class Item < ApplicationRecord
  def self.search(term, fuzzy: false, limit: nil, scope: :all)
    # YAGNI — the test asked for name filtering, not a search framework
  end
end

Over-engineered.

</Bad>

Don't add features, refactor other code, or "improve" beyond the test.

Verify GREEN — Watch It Pass

MANDATORY.

bundle exec rspec spec/models/item_spec.rb

Confirm:

• Test passes
• Other tests still pass
• Output pristine (no errors, warnings)

Test fails? Fix code, not test.

Other tests fail? Fix now.

REFACTOR — Clean Up

After green only:

• Remove duplication
• Improve names
• Extract helpers

Keep tests green. Don't add behavior.

Repeat

Return to the feature spec. Next error drives the next piece. Drop to unit tests when needed. Continue until the feature spec is green.

Good Tests

| Quality | Good | Bad | | ---------------- | ----------------------------------- | ------------------------------------------------ | | Minimal | One thing. "and" in name? Split it. | it "validates email and domain and whitespace" | | Clear | Name describes behavior | it "test1" | | Shows intent | Demonstrates desired API | Obscures what code should do |

Why Order Matters

"I'll write tests after to verify it works"

Tests written after code pass immediately. Passing immediately proves nothing:

• Might test wrong thing
• Might test implementation, not behavior
• Might miss edge cases you forgot
• You never saw it catch the bug

Test-first forces you to see the test fail, proving it actually tests something.

"I already manually tested all the edge cases"

Manual testing is ad-hoc. You think you tested everything but:

• No record of what you tested
• Can't re-run when code changes
• Easy to forget cases under pressure
• "It worked when I tried it" ≠ comprehensive

Automated tests are systematic. They run the same way every time.

"Deleting X hours of work is wasteful"

Sunk cost fallacy. The time is already gone. Your choice now:

• Delete and rewrite with TDD (X more hours, high confidence)
• Keep it and add tests after (30 min, low confidence, likely bugs)

The "waste" is keeping code you can't trust. Working code without real tests is technical debt.

"TDD is dogmatic, being pragmatic means adapting"

TDD IS pragmatic:

• Finds bugs before commit (faster than debugging after)
• Prevents regressions (tests catch breaks immediately)
• Documents behavior (tests show how to use code)
• Enables refactoring (change freely, tests catch breaks)

"Pragmatic" shortcuts = debugging in production = slower.

"Tests after achieve the same goals — it's spirit not ritual"

No. Tests-after answer "What does this do?" Tests-first answer "What should this do?"