We’ve all heard about AI for software testing from some seriously smart people, but there has been a lot of confusion about the idea. This article tackles some of the questions you might be asking: Do I need to be a genius to use AI for software testing? Is AI going to replace me as a tester? Where does AI fit into my testing strategy? With a simple analogy of training a dog, learn how AI fits into testing.
“AIOps” stands for “artificial intelligence in IT operations,” or using machine learning and data science to solve IT problems. AI can help with many IT functions, including detecting and remediating outages, monitoring availability and performance, and IT service management. Like with DevOps, a tester plays an important part with AIOps—they just have to determine what that is.
DevOps does speed up your processes and make them more efficient, but companies must focus on quality as well as speed. QA should not live outside the DevOps environment; it should be a fundamental part. If your DevOps ambitions have started with only the development and operations teams, it’s not too late to loop in testing. You must integrate QA into the lifecycle in order to truly achieve DevOps benefits.
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.
The internet of things (IoT) continues to proliferate as connected smart devices become critical for individuals and businesses. Even with test automation, performing comprehensive testing can be quite a challenge.
Because enterprise applications are highly interconnected, development in stages puts a strain on the implementation and execution of automated testing. Service virtualization can be introduced to validate work in progress while reducing the dependencies on components and third-party technologies still under development.
Melissa Benua, director of engineering at mParticle, chats with TechWell community manager Owen Gotimer about the importance of whole team quality, how to get started using the test pyramid, and how developers can start writing testable code.
Dan McFall, president and CEO at Mobile Labs, chats with TechWell community manager Owen Gotimer about trends in enterprise mobility, the role DevOps and the cloud play in mobile application testing, and the transition to working from home.
Max Saperstone, director of test and automation at Coveros, chats with TechWell community manager Owen Gotimer about codeless automation, using ROI to drive test automation decisions, and why manual testing is here to stay. Continue the conversation with Max (@max) and Owen (@owen) on the TechWell Hub (hub.techwell.com)!
One of the lines in the Agile Manifesto is "Working software over comprehensive documentation." This doesn't mean that no documentation is produced, but instead that only documentation that brings value to the team and the customer should be created.
The rise, fall, and resurrection of Selenium IDE begs the question: Can codeless testing actually scale? Test automation folklore is full of horror stories of failed attempts to apply record-playback tools to perform UI-based functional testing. Putting these stories aside for a moment, let's take an objective look at record-playback tools and compare them with programming-based automation tools in order to evaluate their applicability to functional and visual test automation. Join Moshe Milman as he dives into a hands-on demo of the new Selenium IDE, reviews some of its new capabilities, and goes over the latest open source and commercial tools and trends in the codeless test automation space. Find answers to questions around codeless test automation and discover best practices that will help you to scale your automated tests.
We are often reminded by those experienced in writing test automation that code is code. The sentiment being conveyed is that test code should be written with the same care and rigor that production code is written with. However, many people who write test code may not have experience writing production code, so it’s not exactly clear what is meant. And even those who write production code find that there are unique design patterns and code smells that are specific to test code. Join Angie Jones as she presents a smelly test automation code base littered with several bad coding practices and walks through every one of the smells. She'll discuss why each is considered a violation and via live coding, she will demonstrate a cleaner approach. While all coding examples will be done in Java, the principles are relevant for all test automation frameworks.