Service · Software testing and QA

Test automation

Automation earns its keep where the same checks are repeated over and over. If you ship a new version once a quarter, the money is better spent elsewhere. If you ship weekly, manual regression becomes the slowest link in the whole process and ends up deciding when customers see a new feature.

Faster
than manual regression
Every build
checked without anyone asking
Selection
what matters, not everything
Result
which step failed and why

Included in this service

We do not automate everything. We automate what recurs often and has stopped changing. Chasing one hundred per cent coverage costs more than it returns.

Talk the scope through with an engineer

Business case

We work out how many hours a month manual regression takes today and compare that with the cost of writing and maintaining tests. Sometimes only part of it is worth automating.

UI tests

Playwright or Cypress for web applications, Appium for mobile. Selectors rely on dedicated test attributes rather than CSS classes, so recolouring a button does not knock over half the suite.

API tests

Checks at the interface level run faster and more reliably than clicking in a browser. Anything that does not need a screen moves there: discount logic, VAT calculation, order statuses.

Test data

Each run creates the accounts and orders it needs and cleans up afterwards. Tests do not trip over one another and never touch real personal data.

CI integration

Tests start on every merge request in GitHub Actions, GitLab CI or Azure Pipelines. A red result blocks deployment before the bug reaches production.

Reporting

A screenshot and recording from the point of failure, plus a notification in a Teams or Slack channel. The developer sees immediately whether it was their change or an environment issue.

How we work together

When the first tests go live in the pipeline is agreed in the plan. The team feels real relief once the main checkout and login journeys are covered.

01

Review of existing tests

We look at what you already have, what is flaky and what deserves to stay. There is no need to start from scratch if it can be avoided.

02

Foundations

Project structure for the test code, cloud execution, data handling and reports.

03

Coverage

Tests are written starting with the journeys whose failure hurts most, and every week we show what now runs automatically.

04

Upkeep

Tests are updated as the product changes, and any that raise false alarms are dealt with straight away.

A flaky test is worse than no test. If it fails now and then for no real reason, the team stops reading results and genuine defects vanish in the noise. We fix such tests immediately or delete them without regret. The goal is a green pipeline that everybody trusts.

Questions and answers

No. A script repeats, quickly and tirelessly, what someone has already described. A new and unknown problem in a fresh feature is caught by a person. Automation removes routine from people, not jobs.

With infrequent releases, prototypes and an interface rebuilt every month. In those cases tests need rewriting faster than they can pay back.

Sensible rather than maximal. The journeys the business earns money on, plus places where bugs have already occurred, are usually plenty. Chasing a percentage leads to tests written for the sake of a statistic.

We can carry on under an ongoing contract, or hand the suite to your team with documentation and an online workshop. The test code lives in your repository from day one, and rights to it are set out in the contract.

Let us automate your testing

Tell us how often you release and how long manual checking takes. We will calculate whether automation will pay off.

Hours
Mon-Fri 8:00-18:00 CET, reply within one working day
Meetings
Online via Teams or Google Meet

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