There are many established ideas for ways to test software, but the industry is changing every day, and there's plenty of room for growth of new ideas—or challenges to traditional ones. Here are three ideas for "wish-list" research to conduct in order to shake up some of the conventional notions you may have about software testing techniques.
Testing continuous technological change can seem like chaos. There are many challenges that need to be managed, such as unavailability of power, excessive temperature, incorrect configuration, unexpected behavior of services, network downtime, and processing slowdown in production. By deliberately engineering chaos, we’ll be able to discover many of our systems’ weaknesses before our users do.
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.
Thought leaders from the software community are taking over the TechWell Hub for a day to answer questions and engage in conversations. Michael Bolton, a speaker and thought leader in the testing industry, hosted this Slack takeover, which led to discussions about test exploration, tools, and testers as gatekeepers.
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.
Greg Paskal, evangelist in testing sciences and lead author for RealWorldTestAutomation.com, chats with TechWell community manager Owen Gotimer about testing as a craft, choosing the right test automation tools, and current testing trends around the world.
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.
Paul Merrill, a principal software development engineer and consultant at Beaufort Fairmont LLC, believes that with all the tools and options available for testing, it's important to educate yourself. He discusses when it is appropriate to use certain tools based on varied test situations.
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...