Software quality assurance
QA and testing get used interchangeably often enough that the distinction between them tends to blur. Testing is one specific activity: actually executing a check against the software and observing whether it behaves the way it should. QA is the broader set of processes around that activity, reviewing requirements for gaps before development starts, defining what "done" and "tested" actually mean for a piece of work, planning what level of coverage a feature needs, and auditing whether the development process itself is catching the problems it's supposed to catch. You can run tests without any real QA process behind them, and a QA process includes plenty of work, like a requirements review or a retrospective, that isn't testing at all.
In practice, a QA process typically covers reviewing requirements for ambiguity or gaps before a developer starts building against them, setting a shared standard for what counts as done and adequately tested, planning which parts of a feature need unit coverage, integration coverage, or manual exploration, and tracking a defect back to its root cause so the same class of bug is less likely to slip through again.
QA has historically been a process- and people-focused discipline. Quality engineering is a more recent evolution aimed at the same underlying goal, confidence that software works as intended, but built more through code, automation, and tooling than through manual process alone.
What QA typically covers
- Reviewing requirements for ambiguity or gaps before development even starts.
- Defining a clear standard for what "done" and "tested" actually mean for a given piece of work.
- Planning what level of testing a feature needs, unit, integration, manual, and where.
- Auditing whether the development process itself, not just the software, is actually catching problems it's supposed to.
- Tracking defects back to a root cause, so the same class of bug is less likely to happen again.
Where it shows up
- A QA review of a requirements document, catching an ambiguous spec before a developer builds the wrong thing.
- A retrospective after a bug reaches production, asking why the process didn't catch it rather than just fixing the bug itself.
- A defined checklist a feature has to clear, code review, test coverage, documentation, before it's considered ready to ship.
- A QA lead deciding which parts of a release need manual exploratory testing versus automated regression coverage.
Benefits and challenges
| Benefit | Challenge |
|---|---|
| Prevents a defect from being introduced in the first place, rather than only catching it after the fact. | Harder to measure directly than a pass or fail test result, the value shows up as fewer problems, which is hard to prove a negative on. |
| Gives a team a consistent standard for what quality actually means, instead of leaving it to individual judgment. | Can turn into overhead if it's treated as paperwork rather than genuinely applied, a checklist nobody believes in doesn't prevent anything. |
| Improves the development process itself over time, not just the current release. | Needs buy-in across a team, a QA process that only one person follows isn't really a process. |
Frequently asked questions
What's the difference between QA and testing?
Testing is one specific activity, actually running software and checking whether it behaves correctly. QA is the broader set of processes around that, reviewing requirements, defining standards, planning coverage, and improving the development process itself, of which testing is just one part.
Is quality assurance the same as quality control?
Not quite, though the terms get used loosely. Quality assurance is generally about the process, preventing defects through how work gets built and reviewed. Quality control is more about inspecting the finished product for defects, which overlaps closely with what testing actually does.
Does having a QA team mean developers don't need to think about quality?
No, and treating it that way tends to backfire. A QA team can catch a lot, but the earlier a problem is caught, ideally before it's even built, the cheaper it is to fix, which is part of why quality engineering pushes some of that responsibility earlier into development itself.
How Klarent helps
Klarent's AI agents support the testing side of a QA process, generating and maintaining automated coverage so a team's broader QA process has reliable, up-to-date test results, tracked in Klarent's test management solutions, to actually plan and review against.