What This Is
Automated testing is the engineering discipline of writing tests that run themselves on every commit, before every merge, and as part of every deploy. Regressions get caught by machines instead of by users. It is the work of building a test suite, the CI infrastructure to run it, and the team practices that keep it green over time.
This is the umbrella service that the rest of the testing pages sit under. We design the strategy (what to test and at which layer), build the suites (unit, integration, end-to-end), and configure the pipeline that runs them automatically. The goal is a system where merging a change is safe by default, because the suite either confirms the change works or blocks the merge.
We run automated testing on our own platform across four parallel checks on every push: PHPUnit, Pint, PHPStan, and a frontend build. None of them are optional. Master deploys only proceed when all four pass. The same discipline, automated, blocking, and continuous, is what we set up for clients.
When You Need This
Automated testing becomes essential when manual checks stop scaling. The triggers are usually one of:
- Your team is shipping more frequently and human regression checks are no longer keeping up
- You have had regressions reach production that should have been caught, and you want to make sure the same class of bug cannot recur
- You are onboarding new developers and need a safety net so they can change unfamiliar code with confidence
- You have an MVP that worked when you launched it and now needs to evolve without breaking what already works
- Your team is afraid to refactor because the consequences of breaking something are unclear. Automated tests remove that fear by making the consequences visible immediately.
This is not the right service if you want a one-time test sprint with no ongoing engagement. A test suite that nobody runs or maintains is worse than no tests at all. It gives false confidence and decays into noise. We build suites we expect the team to keep running.
How We Work
Start with money and permissions, add a test for every bug found, keep the suite fast enough that people run it, and wire it into the pipeline so nothing ships red.
A small reliable suite covering what matters beats a large flaky one covering everything, and it is the version that still exists in two years.
The wider picture across test types is on the testing page.
What You Get
- Test strategy document describing what is tested at each layer and why
- Initial test suite covering the highest-risk paths, written to your stack’s idioms (PHPUnit, Vitest, Playwright, etc.)
- CI pipeline configuration that runs tests on every push and blocks merges on failure
- Coverage reporting so the team can see what is and is not protected
- Quarantine and retry strategy for handling flaky tests without disabling them entirely
- Developer documentation on how to add new tests and debug failures
- Optional ongoing retainer for keeping the suite healthy as the system evolves
Technologies We Use
- PHPUnit for PHP backend testing, with unit and feature suites using database transactions for isolation
- Vitest or Jest for JavaScript and TypeScript testing
- Playwright for cross-browser end-to-end testing
- Pest when teams prefer its syntax over PHPUnit
- Bitbucket Pipelines, GitHub Actions, or GitLab CI for CI orchestration
- Codecov or equivalent for coverage tracking
We pick tooling that matches your existing stack rather than imposing our preferences.
Related Systems
Automated testing protects every system we build. A client portal with role-based access cannot be safely refactored without integration tests proving the access rules still hold. A reporting dashboard with complex queries needs unit and integration tests to prevent silent data regressions. The more critical the system, the more it needs the safety net automated testing provides.
Talk to Us About Your Test Strategy
Automated testing sits at the foundation of our software testing services. If your team is shipping into production with no automated safety net, or with a suite that nobody trusts, get in touch and we will scope a path from where you are to a suite that actually works. Our guide to setting up automated testing also covers the practical steps if your team wants to do some of the groundwork first.
What You Are Actually Buying
Not fewer bugs today. A careful developer would have caught most of those anyway.
The ability to change the system later without fear.
In an untested system every change carries unknown risk. Nobody can say what depends on the thing being modified, so changes get made cautiously, tested by hand, and often avoided. Development slows permanently and the slowdown compounds as the system grows.
In a tested system, a change that breaks something unrelated is reported in seconds, by name. Developers work confidently, and refactoring becomes routine rather than risky.
The cost is paid at the start and the return arrives across the whole life of the system. Which means the case is weakest for something short-lived and strongest for anything you intend to keep.
What To Test First
Not everything. In order:
Anything touching money. Pricing, invoicing, payments, discounts, tax.
Anything touching permissions. Who can see and do what.
The paths customers actually use. Checkout, signup, the core task.
Anything that has broken before. A test written after a bug is the highest-value test you will write, and adding one every time is the habit that separates teams that improve from teams that repeat.
Anything with awkward rules. The calculation with seven conditions nobody fully remembers.
What Coverage Does Not Tell You
Coverage measures whether code ran during a test, not whether anything meaningful was checked. Tests can execute a great deal and assert almost nothing, producing excellent numbers and catching nothing.
Chasing a high figure tends to produce exactly those, because the remaining uncovered code is usually the awkward part that is genuinely hard to test.
Eighty percent covering the parts that matter is worth far more than ninety-five achieved by testing trivia.
What Moves The Price
Whether the system was built to be testable. Code with logic tangled into the interface is expensive to test and that expense is a symptom worth knowing about.
How much external dependency there is. Tests touching payment providers or third-party APIs need those faked, which is work.
Whether you want browser-level tests, which are slower, more brittle and more valuable for the few journeys that earn money.
Retrofitting versus building alongside. Adding tests to an existing untested system is significantly more work than writing them as you go.
Where This Goes Wrong
A suite nobody runs. Tests not wired into the pipeline are documentation.
Flaky tests. A suite that fails randomly one run in twenty trains everybody to re-run failures rather than investigate them, which destroys the value of every test you have.
Testing the wrong layer. Elaborate browser tests for logic that a fast unit test would cover better.
Writing tests to hit a number rather than to catch the things that would hurt.
Questions To Ask Whoever Builds It
- What is tested, and does it include payments and permissions?
- Do the tests run automatically on every change, and can anything ship if they fail?
- How long does the suite take? Beyond ten minutes people stop running it locally.
- How often does it fail for no reason? Ask directly.
- When something broke in production, was a test added?
A Brief You Can Send Anyone
The system: [what it does, roughly how big]
What breaking would cost: [and which part specifically]
What has broken before: [the recurring ones]
Whether tests exist now: [any, none, or unknown]
How often you release: [and how nervous that is]
What must never be wrong: [money, permissions, compliance]
