Test strategy
Deciding what to verify at which layer, so coverage is meaningful rather than merely large.
Engineering, Quality & Transformation
Quality Engineering & Test Automation
Manual regression testing does not scale: it grows with the product, gets compressed when deadlines arrive, and is skipped precisely when the release is riskiest.
Build layered automated verification — unit, integration, end-to-end, performance, and accessibility — so a release decision rests on evidence rather than optimism.
Overview
Confidence should be produced, not felt
Every team wants to know whether a change is safe to ship. Without automated verification the answer comes from experience and hope, and the cost of finding out otherwise lands on customers.
We build verification in layers, weighted towards the fast and cheap: unit and integration tests for logic, a focused set of end-to-end journeys for the paths that matter, and explicit performance and accessibility checks where the requirement is real.
What this includes
Quality Engineering & Test Automation capabilities
A strategy review, a new suite, and performance work are separable; scope follows what currently reaches production untested.
Automated test suites
Unit, integration, and end-to-end tests written to be stable, fast, and diagnosable when they fail.
Performance Engineering
Profiling, load testing, and targeted optimisation of the paths where latency actually affects users.
Accessibility Engineering
Automated and manual accessibility validation — keyboard, focus order, semantics, contrast — integrated into the pipeline.
Quality gates in CI
Tests, static analysis, and formatting enforced automatically on every change.
What you receive
Concrete deliverables
- Test strategy and coverage plan
- Implemented automated suites across the agreed layers
- Performance baseline and optimisation report
- Accessibility validation findings and remediation plan
Why it matters
Practical outcomes
Release decisions use evidence
The suite answers whether a change is safe rather than an individual’s judgement.
Regressions surface early
Problems are found in CI, where fixing them is cheapest.
Performance has a baseline
Measured behaviour makes degradation visible instead of anecdotal.
Accessibility stays fixed
Automated checks prevent a corrected issue from quietly returning.
Scope and third parties
Test suites run on third-party browsers, CI platforms, and device or browser services under their own terms and quotas. Automated testing reduces the risk of a defect reaching production and makes regressions visible; it does not prove software is free of defects, and no such assurance is offered.
How a quality engagement runs
From release anxiety to evidence you can point at.
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Review risk and existing coverage
Identify where failures actually occur and where existing coverage is absent or misleading.
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Agree the test strategy
Decide what belongs at unit, integration, and end-to-end level so the suite stays fast and meaningful.
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Implement the suites
Build automated tests that are deterministic, readable, and cheap enough to run on every change.
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Add performance and accessibility checks
Add the non-functional verification that manual testing consistently misses.
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Gate the pipeline
Wire the suite into the pipeline so a regression blocks the merge rather than reaching a user.
What we hold ourselves to
A test suite nobody trusts is worse than none.
These are the commitments that make automated verification something a team relies on rather than reruns.
- 01
Determinism before coverage
An intermittent test is treated as a defect, because a flaky suite teaches people to ignore failures.
- 02
Coverage placed where risk is
Tests concentrate on the logic that breaks and costs money, not on reaching a headline percentage.
- 03
Fast enough to run on every change
Suite runtime is managed deliberately, since a slow suite is a suite that gets skipped.
- 04
Accessibility verified automatically
Automated checks catch the regressions that manual passes miss between releases.
- 05
Failures that explain themselves
A failing test names what broke, so diagnosis does not start with reading the test.
Relevant technology
What layered verification uses
Testing frameworks across levels, the pipeline that runs them, the interfaces under test, and the monitoring that catches what escaped.
Capability domain
7 tools
Testing
- Pest
- PHPUnit
- Playwright
- Cypress
- Vitest
- Jest
- Postman
Capability domain
6 tools
DevOps
- Docker
- Kubernetes
- GitHub Actions
- Terraform
- Linux
- Nginx
Capability domain
8 tools
Frontend
- TypeScript
- JavaScript
- Angular
- React
- Next.js
- Vue.js
- Nuxt
- Tailwind CSS
Capability domain
5 tools
Monitoring
- Sentry
- OpenTelemetry
- Grafana
- Prometheus
- Application logging
Scope boundaries
Where this work hands off
Verification borders on security testing, on pipeline work, and on the design decisions that make states testable in the first place.
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Application Security & Hardening
Functional and accessibility verification asks whether the software does what it should. Whether it can be misused is a security question with its own methods.
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DevOps & CI/CD
Tests are only a gate when something enforces them; wiring that enforcement into delivery is pipeline work.
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UI/UX & Product Design
Error, empty and permission states have to be designed before they can be verified, which is why design and test strategy are worth sequencing together.
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Application Maintenance & Support
Building the suite is a project. Keeping it meaningful as the application changes is continuing ownership.
Questions
Useful context before a consultation
Quality questions usually concern where to start, suite maintenance cost, and how coverage relates to confidence.
What coverage percentage should we target?
Coverage is a diagnostic, not a goal. We prioritise the logic and journeys whose failure would actually hurt, and report what is and is not verified.
Can accessibility be fully automated?
No. Automated checks reliably catch a meaningful subset. Keyboard operation, focus order, and screen-reader behaviour still require manual verification.
Can you add tests to an existing codebase?
Yes. The usual approach is characterisation tests around current behaviour first, then targeted coverage of the highest-risk areas.
Will this find every bug?
No, and any promise otherwise would be worth distrusting. Testing narrows risk to a known and shrinking set, and makes regressions visible before release rather than after.
Who runs the tests after handover?
They run automatically on every change in the pipeline. The suite is written to be readable and maintained by your team, not to depend on us to interpret it.
Start a conversation
Discuss quality engineering
Tell us what currently gets tested by hand and which failures would matter most.