Best practices for test automation emphasize reliability, portability, reusability, readability, maintainability, and more. But how can your existing automated test suite adopt these qualities? Should you address these issues with your current tests, or create an entirely new set of tests? Here are some questions that will help you determine if your test automation maintenance program is operating as it should be.
Teams everywhere are looking to speed up testing without sacrificing quality, so once again, some of the top articles last year were about continuous integration, machine learning, and—of course—how to best implement and use test automation. But readers were also interested in what they shouldn't be doing, with two high-ranking articles about test practices we should stop and a tool you may be misusing.
When people do not have good luck with automation, it is hardly ever because of the tool being used, but almost always because of the wrong automation strategy, wrong expectations, and wrong adoption of automation. Automation tools only answer the “how” of automation, while having an automation strategy gives answers to who, where, when, what, and why. Here's why it's so important to have a test automation strategy.
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.
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.
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.
Testing every single thing isn't feasible, so regression testing should be holistic in verification while focused in scope. A good goal is to ensure no regression issue is introduced into a critical business flow. This endeavor can benefit from automation. An automated testing approach specific to reducing regression issues can go a long way toward building a good client relationship and high brand value.
The concept of accessibility has been around for more than twenty years, yet it’s only recently that more companies have started including it in their development efforts. Developers and testers are recognizing the advantages of incorporating accessibility techniques into their processes. Here are some of these methods specific to agile software development, including a handy checklist.
Many testers spend their time doing functional testing and don't come out of this cocoon. But software testing is all about discovering quality-related information to assist stakeholders in making informed decisions, and there are multiple ways to discover information in addition to functional testing. Here are six actions that will help you add more value to your projects.
Getting good test documentation is a consistent challenge. Agile proposes that you should go very light on documentation, and while test documentation does not need to be heavy, it does need to be clear and cover all that the product is intended to do so you can ensure testing is consistent and results are recorded. Here's how to overcome some major barriers to getting good test documentation.