artificial intelligence

Articles

2020 letters and confetti 7 Agile Testing Trends to Watch for in 2020

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.

Nick Karlsson's picture Nick Karlsson
Human eye Using Computer Vision to Reduce Test Automation Blind Spots

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.

Maxim Chernyak's picture Maxim Chernyak
Artificial intelligence bot AI-Driven Test Automation and Your Future

Many software testers are lamenting the impending demise of their jobs thanks to artificial intelligence. But Jon Hagar thinks there's no need to panic just yet. Here, he details some capabilities he's seen in AI, relates how these can be used in software testing, and explains why he thinks most people don't have to worry—although he also explains who should! As usual, it comes down to a willingness to learn new things.

Jon Hagar's picture Jon Hagar
Close-up of computer keyboard Testing AI Systems: Not as Different as You’d Think

AI-based tools have transformed from a vague, futuristic vision into actual products that are used to make real-life decisions. Still, for most people, the inner workings of deep-learning systems remain a mystery. If you don’t know what exactly is going on while the input data is fed through layer after layer of a neural network, how are you supposed to test the validity of the output? It’s not magic; it’s just testing.

Kerstin Kohout's picture Kerstin Kohout

Interviews

Raj Subramanian Testing in an AI World: A Conversation with Raj Subramanian

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.

Owen Gotimer's picture Owen Gotimer
Artificial intelligence brain Why Testers Should Take Control of the AI Narrative: An Interview with Tariq King and Jason Arbon
Video

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.

Jennifer Bonine's picture Jennifer Bonine
Geoff Meyer How Machines Will Impact the Way You Test Software: An Interview with Geoff Meyer

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.

Josiah Renaudin's picture Josiah Renaudin
Jason Arbon The Future of Software Testing with AI: An Interview with Jason Arbon
Video

In this interview, Jason Arbon, the CEO of Appdiff, explains how artificial intelligence is going to change the way we test our software. He talks about why testers shouldn't be afraid that AI will take their jobs and shows how machine learning can actually be approachable.

Jennifer Bonine's picture Jennifer Bonine

Conference Presentations

What’s Our Job When the Machines Do Testing?
Slideshow

Members of the engineering community are beginning to explore the exciting capabilities of artificial intelligence in order to remove even more mundane and manual tasks from our jobs. The next generation of automation within the software development lifecycle comes to us in the form of AI-inspired approaches: analytics, machine learning, and natural language processing. Geoff Meyer refers to this as cognitive automation, and it offers the promise of automating tasks that up until now could only be performed by humans. However, engineering practitioners going down the path of cognitive automation should proceed with caution due to the combination of excessive hype and unprecedented complexities compared to prior stages of automation. Join Geoff as he provides a framework for organizations to use when considering the application of AI to tasks within their SDLC.

Geoff Meyer
Smart Testing with AI Using Data Mining
Slideshow

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.

Lorna Smyth
Storytelling in the Age of AI
Slideshow

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.

Davar Ardalan
STARCANADA Improve Testing of AI Systems with "Grey-Box" Testing Technique
Slideshow

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..

Yury Makedonov

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