Many organizations have problems with consistently tracking and measuring system outages. Issues aren't logged, admins make changes to systems without going through change management, and a high number of issues turn out to be recurring problems. Implementing a performance measurement process calculates system reliability and can help you improve consistency.

Everyone knows a tester's job is to help improve the quality of the software under test. But it gets a little murky when you try to define the boundary between testing and debugging. There's no clear delineation: Some testers would state how to reproduce the bug, write the report, and hand it off, while others learn the code, find the root cause, and even create builds to fix the bugs. How much is useful, and how much is too much?

There’s a bit of hype in terms such as business intelligence, data analytics, and data mining. In testing terms, though, it means working with scripts and databases, often without traditional GUI interaction. But core testing skills—analysis, synthesis, modeling, observation, and risk assessment—will still help you go far in business intelligence testing.

How many times does something seem too obvious to check? Most of the time this normal human response is a handy shortcut. Your brain tries to save you time—but you can’t always trust it. If your code malfunctions, each of those "too obvious to check" thoughts will bias your thinking about what caused the malfunction. We have to commit up front, before our thinking crystalizes, that the code will have to prove to us that it is correct.