The Latest

Kristoffer Nordström, test developer at Northern Test Consulting AB, chats with TechWell Community Manager Owen Gotimer about the rise in popularity of Python as a programming language, the importance of being authentic online and off, and how having fun at work can help increase productivity.

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.

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.

Hans Buwalda, CTO at LogiGear, discusses shifting the paradigm from not moving testing left or right along the software development lifecycle, but testing in a continuous circle to find unexpected problems. He talks about how testing is a mindset, not just a skill, and shares his insight into helping customers get further with Selenium.

Gil Sever, CEO at Applitools, discusses his journey in visual testing to making your product “visually perfect.” He talks about how companies are getting started in using automation, as well as how to get involved in leveraging and implementing AI in visual testing.

Many people misunderstand the purpose of Cucumber. Because it seems to yield clearer, plain-language test scripts, testers want to use Cucumber as a general-purpose testing tool, including for API tests. But its true purpose is as a BDD framework. You may be thinking, what’s the harm? Here’s why it makes a difference—and why you should choose another tool for API testing.

Simple rules are great for guiding us through an overwhelming workload. Sometimes complicated solutions are necessary, but simple rules often outperform complex algorithms, making them more efficient than sophisticated, difficult flows. They can also break down big goals into practical daily guidelines testers can follow to perform more effectively. Let’s see how simple rules can be applied in software testing.