Continuous testing means all your tests are executing all the time, providing continuous feedback into the quality and health of your applications. In order to achieve continuous testing, you must first adopt the right test automation strategy. Understanding how to bring in all different types of test automation practices as efficiently as possible enables you to get started down the path of continuous testing.
Shifting your testing either left or right can meet different needs and improve different aspects. How do you know whether to make a change? Let your test cycles be your guide. Just like when driving a car with a manual transmission, if the engine starts to whine or you’re afraid you’re about to stall out, switching gears may be just what you need.
The earlier you find out about problems in your code, the less impact they have and the less it costs to remediate them. Therefore, it's helpful to move testing activities earlier in the software development lifecycle—shifting it left in the process timeline. This article explores the shift-left methodology and how you can approach shifting left in your organization.
“Shift left” is one of the latest buzz terms in software testing. Movements like agile and DevOps recommend that testers shift left, but what does that mean, exactly? Here's how one tester became a believer in the shift-left movement; how he got his team's developers, analysts, designers, and managers on board; and how his entire organization has benefited from the shift.
QA testers often take on more of a role than just testing software code. When the team needs help, QA should lend a hand in assisting with business analysis, customer communication, user experience, and user advocacy.
In this interview, Dawn Haynes, CEO, testing coach, and consultant for PerfTestPlus, discusses the ever-evolving world of AI and machine learning and the impact on the future of testing. Dawn explains why tools and automation will not be able to replace people, so testers don’t need to worry about job security.
In this interview, Rob Sabourin talks about his STAREAST presentations. These cover how to elicit effective usability requirements with storyboarding and task analysis, and how to blend the requirements, design, and test cycles into a tight feedback loop.
In this interview, Keynote's Josh Galde talks anything and everything mobile. The industry veteran discusses how much of the testing process should be automated, the difference between testing phones and tablets, and what he sees as "the next big thing" in the industry.
In this TechWell interview, Facebook's Simon Stewart digs into his company's shocking approach to testing, which is that they don't have a testing department. He also talks about the challenges and pressure that come along with producing so many different mobile builds per year.
Agile testing is hard. Testers contend with terse requirements, minimal process, little documentation, continually evolving business, technical and organizational factors. Auditors demand proof of compliance. Some teams have trouble conforming to regulations while preserving agile practises..
We're all hearing the buzzwords of AI, machine learning, chatbots, and next-generation testing. Does this mean that the days of traditional testing as we know and practice it are over? Eran Kinsbruner doesn't think so. Join him to learn about the clear transformation happening toward smarter testing techniques and tools. These approaches will drive better pipeline efficiency and release velocity with high quality, and Eran thinks this means good things for the testing practice and practitioners. You'll discover the key trends that are happening around AI, machine learning, and bots in the web and mobile landscapes, and get the ability to identify some early adopters who are taking the lead in these domains.
Speed is king in agile. In a world where most of the agile process is automated, testing is the slowest and most expensive part of getting your app or website deployed to the world. Very few app teams have a decent amount of test automation, and even they still have days of manual testing during each agile cycle before they release new versions of their app. Testing is difficult, especially at the UI level, which is why it is still relegated to humans. But all that is changing with the application of artificial intelligence and machine learning. Join Jason Arbon as he explains how agile testing is ripe for disruption because AI itself is based on examples of input and output—which sounds a whole lot like the testing activity.
Organizations today are required to test their web application across browsers and mobile devices. Choosing the right framework is a matter of organizational as well as technical fit. With a plethora of test frameworks that span across practices such as behavior-driven development, unit...