Quality Engineering
A test suite is not a safety net by default. Slow, flaky suites teach teams to ignore red builds, which is worse than having no suite at all. We build the kind engineers trust enough to act on.
Start from what failure costs
Not all defects are equal. A misaligned button and a mispriced order are both bugs; only one of them ends up in a regulatory conversation. Testing effort should follow that difference, and surprisingly often it does not.
We begin by mapping where failure is genuinely expensive — money movement, permissions, data integrity, anything with a compliance obligation attached. That map decides where deep coverage goes and where a lighter touch is a reasonable trade rather than negligence.
What we do
Test strategy
An explicit decision about what is covered by unit, integration, end-to-end and manual testing — written down, so the shape of the suite is intentional rather than emergent.
Automation that holds up
Deterministic tests with controlled data and no reliance on timing luck. A flaky test is a defect in its own right and we treat it as one.
Pipeline design
Fast feedback on every commit, deeper suites on a schedule. If the pipeline takes an hour, people stop waiting for it, and the feedback stops being feedback.
Performance testing
Load profiles drawn from real traffic, run against production-like infrastructure, with results that point at a bottleneck rather than a verdict.
Security testing
Dependency scanning, static analysis and targeted review folded into normal delivery, so findings arrive while the code is still fresh.
Release practice
Feature flags, staged rollout and monitoring that catches a bad release in minutes. Detection and recovery matter more than the pretence that nothing will slip.
How an engagement runs
Cost the failures
Which defects have actually hurt you, and how much. A test strategy that is not derived from that is decoration, and it will be the first thing cut under pressure.
Fix the feedback loop
Before adding a single test, we get the existing suite fast and honest. A slow, flaky pipeline teaches a team to ignore red builds, which is worse than having no suite.
Test at the cheapest level that works
Most assertions belong under the UI. Browser tests are reserved for the handful of journeys where the integration itself is the risk.
Rehearse the bad release
Deploy something broken on purpose, in a controlled window, and measure how long detection and rollback actually take. Almost nobody knows this number before they measure it.
Give the suite an owner
Flake rate tracked, quarantine rules agreed, and a named person responsible. Unowned test suites rot faster than the code they cover.
What you are left with
Fast core suite
Commit to feedback in under ten minutes, or a written plan for how it gets there.
Flake budget
A tracked rate, a quarantine process, and an owner — not a folder of skipped tests.
Rollback evidence
A measured time to detect and reverse, from a rehearsal rather than an assumption.
Test strategy
One page: what is tested where, what is deliberately not tested, and why.
Signals we watch
The useful measures are about confidence and recovery, not raw counts. How long from commit to feedback. What share of builds fail for reasons unrelated to the change. How quickly a bad release is detected and reversed. How many defects reach production in a category you had decided mattered.
Coverage percentage is not on that list. It is easy to raise and tells you very little about whether a change is safe.
- Commit-to-feedback time under ten minutes for the core suite
- Flake rate tracked and driven toward zero
- Time to detect and reverse a bad release, measured by rehearsal
- Escaped defects triaged by severity, not counted in aggregate
When not to hire us
We will not write you a large regression suite for a product whose direction is still changing weekly. Those tests will be deleted within a quarter, and you will have paid for the privilege.
And if your build takes an hour and nobody trusts it, hiring us to add coverage is the wrong order. Fix the loop first — that is often a week of unglamorous work and it changes everything downstream.
Common questions
Usually repair, selectively. We measure which tests fail intermittently and which actually catch regressions, then delete the ones earning nothing. Suites are often a third smaller and considerably more useful afterwards. A full rewrite is warranted when the tests are coupled to an architecture you are replacing anyway.
Related work
Bring us the part that is stuck.
Send the constraint you are working around and we will come back with an approach, a rough shape of the work, and what it would take to hand it over.