SOFTWARE QA & TESTING — A SUITE PEOPLE ACTUALLY TRUST
A red build nobody investigates is the same as no tests at all.
We build and run test suites that stay green when the software is fine and fail loudly when it isn’t — automated where automation pays, manual where a person is genuinely better, and with flaky tests treated as defects rather than as weather.
✓ Flaky tests fixed, not retried✓ Runs in your existing CI✓ Coverage of risk, not of lines✓ Your team can maintain it
If your team has started rerunning failed builds until they pass, that’s the problem we fix first.
In short: QA is not a phase at the end. It’s a set of checks that run continuously and give a trustworthy answer to one question — is this safe to release? We build that answer for you: automated tests where they earn their maintenance cost, exploratory testing by people where judgement beats a script, and performance work before load becomes an incident rather than after.
The trust problem
There is a moment every struggling test suite passes through. A test fails, someone reruns it, it passes, and the team learns that failures don’t necessarily mean anything. From then on the suite costs money and provides no information.
Flakiness is the cause, and it’s nearly always one of four things: a test that depends on timing, a test that depends on another test having run first, a test sharing data with a parallel run, or a test reaching a real external service. All four are fixable, and none of them get fixed while the team’s habit is to press retry.
So the first thing we do on an existing suite is measure how often each test fails and passes on rerun, then fix or delete the worst offenders. A smaller suite that is always right beats a large one that is usually ignored.
What to automate, and what not to
Every automated test is an asset that also has to be maintained. The question is never “can this be automated” — almost anything can — but whether it will still be worth its upkeep in a year.
AUTOMATE
The paths that make you money
Sign up, log in, search, add to cart, pay, submit. Run on every commit, fast, and treated as a release blocker. If you automate nothing else, automate these — and keep the list short enough that the suite finishes in under ten minutes.
AUTOMATE
Calculations and rules
Pricing, tax, discounts, permissions, eligibility. Cheap to test, expensive to get wrong, and the place where a regression is most likely to reach production unnoticed because it looks fine on screen.
DON’T
Anything still being redesigned
A screen changing weekly generates a broken test weekly, and the team starts deleting tests to make the build pass. Test it by hand until the design settles, then automate it once.
DON’T
Whether it looks and feels right
A script can confirm the button exists. It cannot tell you the flow is confusing, the error message is alarming, or the whole thing feels slow. That is a person’s job and always will be.
The same defect costs a different amount depending on where it’s caught, and the gap is large enough to drive the whole strategy.
Caught by a unit test, it’s a few minutes: the developer still has the code in their head. Caught in review, an hour. Caught in QA, half a day — write the report, reproduce it, context-switch back, retest. Caught in production, it’s the fix plus an incident, plus support handling the calls, plus whatever the wrong behaviour did to real data while it was live, plus the customers who quietly left.
That’s why we push checks as early as they’ll go, and why a fast suite that runs on every commit is worth more than a thorough one that runs nightly. Getting it running early is part of the same work as CI/CD pipelines.
What we won’t do
Chase a coverage percentage
Line coverage measures which code ran, not whether anything was verified. It is possible to reach ninety percent and assert almost nothing. We report coverage of behaviour and risk instead, which is harder to put on a slide and actually means something.
Add auto-retry to make the build green
Retries hide the flakiness rather than removing it, and the underlying race condition is usually a real bug that will surface in production at a worse moment. We fix the test or delete it.
Own your quality permanently
An outsourced QA team that nobody internal understands becomes a bottleneck and then a dependency. We build the suite so your developers can extend it, and we’re happy for the engagement to shrink.
How we start
Week 1 — find out what breaks and what’s flaky
Your last few months of bugs, grouped by where they came from and how they got out. If a suite already exists, we measure per-test failure and rerun-pass rates. Both tell you where to spend before anyone writes a new test.
Weeks 2–3 — the money paths, fast and green
A small suite covering the flows that generate revenue, running on every commit in under ten minutes, with the flaky tests dealt with. Trust gets rebuilt here or not at all.
Week 4 onward — widen, and hand over
More coverage where the bug history says it’s needed, performance testing before the next big release, and pairing with your developers so writing a test becomes part of writing a feature rather than a separate department.
What our clients say
The businesses we’ve built for, in their own words.
★★★★★
“When I approached Abedin Tech with my land share selling plan, I wasn’t sure how it would work. But thanks to their precise strategy and powerful marketing, my business is now thriving. They truly understand their clients’ needs and go above and beyond.”
Owner, Richland Properties
Real Estate
★★★★★
“I approached Abedin Tech to develop my website with several specific functionalities. Their team delivered exactly what I envisioned, creating a beautifully designed website that met all my requirements. I highly recommend Abedin Tech.”
Rohit
Owner, Shop from China
★★★★★
“The decision to partner with Abedin Tech was the best decision we made. Our site looks great, our traffic is through the roof, and our sales are better than ever. Abedin Tech is the perfect digital partner that offers what is beyond your expectations!”
James Anderson
★★★★★
“We had an idea but no sense of direction. With each step of the way, Abedin Tech guided us and turned our vision into a beautiful website with functionality. The outcome is evident by the numbers!”
Isabella Scott
Send us your last three months of bugs
That list tells us more than any conversation about test strategy. We’ll come back with where they came from, which ones a test would have caught, and what a suite covering that would cost to build and to keep.
Our tests fail randomly and everyone just reruns them. Can that be fixed?
Yes, and it is the first thing we tackle. Flakiness is nearly always one of four causes: a test depending on timing, a test depending on another test having run first, tests sharing data across parallel runs, or a test reaching a real external service. We measure each test’s failure and rerun-pass rate, then fix or delete the worst. A smaller suite that is always right beats a large one the team has learned to ignore.
What should we automate and what should stay manual?
Automate the paths that make money — sign up, log in, search, checkout, submit — and the rules that are cheap to test and expensive to get wrong, like pricing, tax and permissions. Keep manual anything still being redesigned, since a screen changing weekly produces a broken test weekly, and anything requiring judgement about whether a flow feels confusing or slow. A script can confirm a button exists; it cannot tell you the experience is bad.
Is a high test coverage percentage a good goal?
No. Line coverage measures which code ran, not whether anything was actually verified — it is entirely possible to hit ninety percent while asserting almost nothing. We report coverage of behaviour and risk instead, which is harder to put on a slide and considerably more informative about whether a release is safe.
Why does catching bugs early matter so much?
The same defect costs radically different amounts depending on where it is caught. In a unit test it is minutes, because the developer still has the code in mind. In review, an hour. In QA, half a day of reporting, reproducing and retesting. In production it is the fix plus an incident, plus support handling calls, plus whatever the wrong behaviour did to live data, plus the customers who quietly left. That gap is why a fast suite running on every commit beats a thorough one running nightly.
Will our own developers be able to maintain the test suite?
That is a design requirement, not an afterthought. A suite only the supplier understands becomes a bottleneck and then a dependency. We write tests your developers can read and extend, and we pair with them so writing a test becomes part of writing a feature. We are content for the engagement to shrink over time.
When should we do performance testing?
Before a launch, a marketing push, or any change to how data is stored or queried — and it is dramatically cheaper then than during an incident. The useful output is not a pass or fail but a number: how many concurrent users before response times degrade, and which specific query or service gives way first.
What testing connects to
A suite is only useful if something runs it and someone ships behind it.
