Writing — page 2 of 4
Which technique finds which bug, how to catch a requirement that cannot be tested, and where AI earns its place in a QA workflow.
A build can hit 95% code coverage and still ship with major requirements never checked. The two metrics answer different questions, and confusing them is how a coverage number stops meaning anything.
A test that fails only sometimes trains a team to stop trusting red. Here are the handful of root causes behind most flaky tests, and the fixes that address the cause instead of adding another retry.
A report that says 'checkout is broken' costs a developer a round trip just to find out what you meant. Here's what a report needs before it goes to anyone else, and the severity/priority confusion that stalls a fix without anyone noticing why.
A test that fails because the data underneath it is wrong looks identical to a real bug, and costs just as much time to diagnose. This post covers the three ways teams get data into a test environment, what each is actually good for, and the specific way each one breaks.
A criterion that needs a conversation to score isn't a criterion, it's a placeholder for one. Here is what separates a testable acceptance criterion from one that just looks like it, with the Given/When/Then format worked through on a real example.
Scripted test cases and AI-generated ones only exercise what someone thought to write down. Exploratory testing finds the rest, at the cost of leaving less of a paper trail. Here's how session-based structure keeps it accountable without scripting away the point of it.
Every AI test case generator claims to save your QA team hours. Few say which input they're built for or what happens once the cases land in your tracker. This post sorts the category into four types and gives you a checklist to run against any of them, including Casely.
Five inputs with a handful of values each produce thousands of combinations, more than anyone will run. Pairwise testing picks a small set of cases that still exercises every pair of values together, and this post works through how that set gets built and what it leaves untested.