A growing company was tasked to develop a test automation program from scratch, change its coding practices, and build a continuous testing toolchain. Martin Ivison details how they did it, including realizing that implementing the traditional test pyramid wasn't going to work—it would have to be turned upside down. They found out that small is beautiful, cheap is good, and cultural change matters.
Many software testers are lamenting the impending demise of their jobs thanks to artificial intelligence. But Jon Hagar thinks there's no need to panic just yet. Here, he details some capabilities he's seen in AI, relates how these can be used in software testing, and explains why he thinks most people don't have to worry—although he also explains who should! As usual, it comes down to a willingness to learn new things.
Whole-team testing means the whole team understands and participates in testing, using testing education as a tool to support quality efforts. And to be able to support testing in a meaningful way, team members must experience how testing is done by professional testers. Understanding skilled testing can help non-testers realize what quality criteria should be there and what elements of a product contribute to great quality.
Talia Nassi, a software engineer at WeWork, discusses why testing in production is such a controversial topic. She talks about why people fear the process and how a change with intention would increase confidence in your team. Talia also shares how the Women Who Test community supported her and helped constitute the life and career she has today.
Shachar Schiff, founder and principal consultant at BadTesting, chats with TechWell community manager Owen Gotimer about the recent rebrand of BadTesting, the four archetypes he uses to help customers, and the universal importance of communication.
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.
A command-line package installer is a handy tool that installs your desired software package without a fancy UI, yet it often proves to be more effective than some tools integrated into expensive IDEs. Brew and Pip are two of the more popular options for package installers when using the script language Python. But what’s the difference between them, and which makes more sense for your use? Here’s an introduction to Brew and Pip for testers.
Quality and testing consultant Isabel Evans discusses shifting testing left. She says shifting your mindset along with your testing activities will make all the difference in embracing this change, because how you think about testing is more important than when you do it. Isabel also talks about constantly testing and observing in order to make sure we are delivering the right thing to our customers.
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.
AI-based tools have transformed from a vague, futuristic vision into actual products that are used to make real-life decisions. Still, for most people, the inner workings of deep-learning systems remain a mystery. If you don’t know what exactly is going on while the input data is fed through layer after layer of a neural network, how are you supposed to test the validity of the output? It’s not magic; it’s just testing.