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4 Advantages of Applying AI in Software Testing We’re always looking for smarter, faster, better ways of testing. As the popularity of artificial intelligence grows, more and more testers are realizing its capacity to make cumbersome and time-consuming tasks simpler. AI is coming, so we should take advantage of it. Here are four benefits to applying AI in testing. |
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Choosing the Right Tools for the Job The saying “If all you have is a hammer, everything looks like a nail” summarizes a cognitive bias we have to use tools that are most familiar to us, even if they are the wrong tools for the job. Software professionals often fall into this trap. Here are some tips on how to choose the right tools for your projects. |
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Visual Regression Testing: A Critical Part of a Mobile Testing Strategy Despite our best efforts to replicate customers' behavior in our test automation suites, teams often forget about nonfunctional requirements. An important one is visual perception—how users see and feel each application they use. Visual regression testing can fill a significant gap in user experience expectations. |
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2 Quick Wins for Building Context in Testing Testers fill in their assumptions about the project, domain, and technology with things they learn while testing and while talking with people. Sometimes the information they learn is good, but sometimes they miss something important. Here are two quick wins for filling in those assumptions with good information. |
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6 Steps to Achieve Realistic, Reliable Load Testing Simulating real users’ behavior gives you a transparent picture of your software's load capabilities. To reproduce users' actions accurately, you can use a request flow design from when the system is in the production environment. Here are six steps for achieving the most realistic load for your load testing process. |
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The AI Testing Singularity Machine learning is rapidly growing more powerful, already sometimes imitating the actions and judgments of humans better than humans. In the near future, even before machines are conscious, they will be able to mimic human software testers. What will be the impact of AI on testing? Jason Arbon has a bunch of ideas. |
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Leveraging Kubernetes as a Tester Kubernetes is a scalable, production-grade container orchestration tool with automated deployment, scaling, and management capabilities. Using it shortens the feedback loop and enhances communication. Here’s how testers can leverage Kubernetes to quickly gauge application quality and speed up the delivery of value. |
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NSA Adds to Open Source Tools and Tech Transfer Program The National Security Agency recently released several of the agency’s software tools as open source and added new technologies to the NSA technology transfer program patent portfolio that are ready for licensing. Could leveraging any of these technologies help your efforts? |