artificial intelligence

Articles

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
Brain made out of a circuit board Leveraging Machine Learning to Predict Test Coverage

Test coverage is an important metric within test management, and as technology evolves, we‘re able to leverage new trends to predict coverage. Weka, an open source suite of machine learning software, can take your test management beyond spreadsheets to the latest AI technologies, letting you predict your test coverage earlier with greater accuracy.

Bhavani Ramasubbu's picture Bhavani Ramasubbu
A robot hand touching a keyboard 5 Things That Will Impact the Future of Software Testing

From the way we look at software, evaluate risks, think about complexity, design our test approach and strategy, and help to release a stable product to the customer, technology has had an influence on how we test software. And that influence will only continue as technology advances. On a high level, here are five key things we’re already seeing that are going to shape the future of software testing.

Raj Subrameyer's picture Raj Subrameyer
Machine learning Testing a Moving Target: How Do We Test Machine Learning Systems?

Most machine learning systems are based on neural networks, or sets of layered algorithms whose variables can be adjusted via a learning process. These types of systems don’t produce an exact result; in fact, sometimes they can produce an obviously incorrect result. So, how do you test them? Peter Varhol tells you what you should consider when evaluating machine learning systems.

Peter Varhol's picture Peter Varhol
Human or machine head The Turing Test: From Star Wars to Modern Software Testing

Hadoop, Splunk, and other modern business intelligence tools and decision support systems all have something of the flavor of artificial intelligence—that is, you ask a question and get an answer. Testing these tools is a challenge, but it can also provide opportunities for testers to shine if they can correctly distinguish an inhuman response.

Michael Mak's picture Michael Mak

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