Many organizations are looking to expand their automation abilities by designing and developing test automation frameworks. However, we often abandon good coding practices in favor of working as fast as possible. We need to treat this project like any other application development project. Here are three of the most important clean coding practices to keep in mind in order to make a scalable test automation framework.

The way we think about what necessitates test coverage being “complete” influences how we test and the cases we create. After all, you wouldn't design tests for situations that don't occur to you—and you can't test what you can't see. It's time to take off the blinders. Here's how you can find where the bugs in your products are occurring, and then adjust your strategy to pinpoint them.

Everyone on the software team has the same goal of delivering the best product they can, so letting testers discover bugs is always good—the more bugs found, the better! But misconceptions often lead to testers getting the bad rap of "breaking" the software. It's a tester's job to think like a user. Developers and stakeholders might call that negative testing, but the result is a better product, and that’s all positive. Let's change the way we talk about testing.

Data analysts have to know a lot about diverse business areas so that our reports provide usable information, not just data. We can use this awareness of the value of information to merge different data sets in order to answer new questions, and even help our users make better decisions. But in order to do this, we need to present not just the data, but the information value represented in that data.