Testing isn’t a checkbox, it’s your safety net.

If you want to ship robust, reliable R packages, you need more than just unit tests. You need a layered approach that covers every angle, from individual functions to the user’s journey, from code coverage to the quality of your tests themselves.

Let’s break down the four essential layers of testing that every serious R package should have.

1. Unit Testing

Start small, think big.

Unit tests are the foundation. They check that each function does exactly what it’s supposed to do, under every condition you can imagine.

• Why it matters: Unit tests catch bugs early, before they snowball into bigger issues. They make refactoring safe and keep your codebase maintainable.
• How to do it: Use testthat to write focused, fast-running tests for each function. Tackle edge cases and boundary conditions.

Unit tests are your first line of defense. They ensure each building block works before you assemble the whole structure.

2. Acceptance Testing

Think like your users.

Unit tests check the parts; acceptance tests check the whole. They validate that your package actually helps users achieve their goals—not just pass technical checks.

• Why it matters: Even if every function works, your package might still fail to deliver value. Acceptance tests catch gaps in workflows and real-world scenarios.
• How to do it: Use cucumber, describe user stories in plain language. Automate these scenarios to ensure your package solves real problems.

Acceptance testing bridges the gap between code and user experience.

3. Code Coverage

Don’t leave gaps.

Code coverage tools tell you which parts of your codebase your tests actually exercise. Untested code is a breeding ground for bugs.

• Why it matters: High coverage means fewer surprises in production. It highlights dead code and risky areas.
• How to do it: Use covr to visualize coverage. Usually the higher score the better, but remember: coverage alone doesn’t guarantee quality.

If you don’t test it, you don’t know it works.

4. Mutation Testing

Test your tests.

Even with high coverage, your tests might be weak. Mutation testing introduces small changes (“mutations”) into your code and checks if your tests catch them. If tests pass despite the bug, you’ve found a weak spot.

• Why it matters: Mutation testing exposes tests that don’t actually protect against real faults. It’s the ultimate reality check for your test suite.
• How to do it: Try muttest to simulate bugs and ensure your tests are truly robust.

Mutation testing asks: are your tests actually guarding the code, or just going through the motions?

The Power of Layered Testing

Each layer—unit, acceptance, coverage, mutation—catches what the others miss. Stack them for confidence and quality.

• Unit tests catch bugs at the source.
• Acceptance tests ensure user goals are met.
• Code coverage highlights what you’re missing.
• Mutation testing checks if your tests are meaningful.

Start with one layer, but aim for all four. Your users—and your future self—will thank you.