What's the point of a QA pass?

It's a structured run through the risky paths with capture recording every failure. Run with capture on, it produces a worklist of fixable failures; run without, it produces impressions you can't act on. The capture is what makes the activity pay off.

How do I make a QA pass pay off?

Run it with capture on, group the failures it produces, fix the highest-impact one first, and tie failures to builds so you can verify the fix. Plan it as a loop — capture, group, fix, verify — rather than a one-off.

How to Plan a QA Pass

Q: How do I plan a QA pass?

Remember it's a structured run through the risky paths with capture recording every failure, and set it up to produce actionable data. Walk a checklist of the awkward states with capture on and triage what it finds. Run it with automatic crash capture on so it generates a ranked list of real failures rather than vague impressions.

Quick answer: To plan a QA pass, remember what it is for: a structured run through the risky paths with capture recording every failure. Walk a checklist of the awkward states with capture on and triage what it finds. The key is to run it with automatic crash capture on, so it produces real, grouped, build-tagged data — a list of fixable failures — rather than vague impressions you can't act on.

Planning a QA pass is mostly about making sure it produces something actionable. At its core, a QA pass is a structured run through the risky paths with capture recording every failure. Run without capture, it generates impressions; run with capture, it generates a ranked list of real failures. That difference is the whole point. This guide covers how to plan a QA pass so it pays off: Walk a checklist of the awkward states with capture on and triage what it finds.

Planning a QA pass

The purpose of a QA pass is clear once you state it: it is a structured run through the risky paths with capture recording every failure. Planning it well means setting it up to produce data you can act on. Walk a checklist of the awkward states with capture on and triage what it finds. The most common mistake is running the activity without capture, so it surfaces a feeling that “something broke around there” instead of a specific, reproducible failure.

So the first planning decision is to run a QA pass with automatic crash capture on. Then every failure it provokes is recorded with its stack trace, the build, the device, and the breadcrumb trail — which turns the activity from a source of impressions into a source of fixes.

The silent majority who never report anything

For every player who files a report, a large number simply hit the problem, sigh, and close the game. They do not owe you a bug report, and most will not write one. The failures that churn the most players are therefore the ones least likely to ever reach your inbox, which is a deeply unfair feedback loop: the worse the bug, the quieter it tends to be.

The only way out of that loop is to stop depending on goodwill. When every crash is recorded automatically, the silent majority become data. You finally see the failure that is quietly costing you installs, ranked by how often it actually happens rather than by who happened to be patient enough to complain.

Why “it works on my machine” is a trap

Your development machine is the single least representative device your game will ever run on. It is the one configuration guaranteed to work, because you built and tested the game on it. Your players live out on the long tail of GPUs, drivers, operating-system versions, resolutions, and background software, and that long tail is exactly where the failures you never reproduce are hiding.

This is why local testing, however thorough, has a hard ceiling. You cannot own every device, and you cannot imagine every combination. Field data closes that gap by letting the failures come to you with the configuration attached, so a crash that only happens on one driver version stops being a mystery and becomes a one-line filter.

Why the report you get is never the whole story

When a player does take the time to tell you something broke, the message is almost always thin: “it crashed,” maybe a screenshot, rarely a version number, and almost never the exact steps. You are left reconstructing the scene of an accident from a single blurry photo. The information you actually need to fix the bug — the stack trace, the device, the build, the state the game was in — is precisely what a human report leaves out.

That is why working from manual reports alone keeps you slow. Every ticket becomes a back-and-forth interrogation, and half the time the player has moved on before you get an answer. Automatic capture removes the interrogation entirely, because the context travels with the failure the instant it happens.

Turning it into fixes

With capture on, a QA pass produces a worklist rather than a vibe. Group identical failures so the highest-impact one is on top, read its trace and breadcrumbs, fix the root, and tie failures to builds so you can confirm it. Because you always work the biggest-impact failure first, the activity pays off fast.

Make it part of a loop. a QA Pass is most valuable when its findings flow straight into fixes you verify against the next build, rather than into a document no one revisits. Plan it that way — capture, group, fix, verify — and it becomes a reliable way to make the game more stable, not just a box you ticked.

This is where a tool like Bugnet earns its place. Its SDK captures every failure automatically with the full stack trace plus device, OS, memory, build, and game-state context, folds identical failures into one grouped issue with an occurrence count, and ties each to the build it happened on. The result is that the abstract idea above stops being theory and becomes a ranked list you work down — the worst problem first, verified fixed when its signature disappears from the next release.

Most of the failures hurting your game are silent. The first job is making them visible; the fixes get a lot easier after that.