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.
With 2020 upon us, software development firms seeking to increase their agility are focusing more and more on aligning their testing approach with agile principles. Let’s look at seven of the key agile testing trends that will impact organizations most this year.
The standard test automation toolkit easily completes web and mobile automation, but it fails to detect elements on desktop and mobile content-based applications. Computer vision (CV) replicates the human eye using deep learning technology and can determine objects in pictures, which helps machines orient in space and perform repetitive detection tasks. Let's see how CV can help automate the testing of a much wider software product list.
Davar Ardalan, founder and storyteller-in-chief of IVOW, talks about how her experience working at NPR helped her launch an AI and storytelling startup. She also discusses how testers, QA analysts, and software engineers are on the front lines of working with users and understanding user engagement, and she explains the importance of finding ways to collaborate with them.
Raj Subramanian, developer evangelist at Testim.io, talks about artificial intelligence; the differences between AI, machine learning, and deep learning; and what AI means for the future of software testing.
In this interview, Tariq King, the senior director and engineering fellow for quality and performance at Ultimate Software, and Jason Arbon, the CEO of test.ai, explain the role artificial intelligence plays in modern testing and why you should establish a foundation right now.
In this interview, Geoff Meyer, a test architect in the Dell EMC infrastructure solutions group, discusses whether or not testers should be nervous about artificial intelligence, what testers can do right now to keep up with the times, and when AI is most useful for software teams.
The engineering community is beginning to explore the exciting capabilities of AI in order to remove even more mundane and manual tasks from our jobs. Join Geoff Meyer as he provides a framework for organizations to use when considering the application of AI to tasks within their SDLC.
The approaches to testing are continuously evolving as we try to keep up with the application needs of today’s users. Our industry is facing a new paradigm where AI is helping achieve scale, coverage, and business impact for many organizations.
People are actively engaging in civic tech, social robots are tweeting, and veteran storytellers are capturing stories in new ways using virtual and augmented reality. This explosion of tools, sources, voices, and data is indicative of a new, more collaborative era for storytelling.
There are two main challenges to testing systems that incorporate elements of artificial intelligence. First, the same input can trigger different responses as an AI system learns and adapts to new conditions, and second, it is difficult to understand what the correct response really should..