Discover how AI and machine learning reduce flaky tests, cut maintenance costs, and improve accuracy in modern automated testing.

In this article, let’s explore how machine learning is revolutionizing software testing and breaking new ground for QA teams and enterprises alike, as well as how to successfully implement it.

With machine learning, we can reduce maintenance efforts and improve the quality of products. It can be used in various stages of the software testing life-cycle, including bug management, which ...

Let’s review how machine learning has developed, and then explore how ML techniques are radically changing the software testing industry.

Machine learning systems operate in a data-driven programming domain where their behaviour depends on the data used for training and testing. This unique characteristic underscores the importance of ...

When testing machine learning systems, we must apply existing test processes and methods differently. Machine Learning applications consist of a few lines of code, with complex networks of ...

I then looked a step further and researched testing capabilities based on data, analytics, and machine learning that development teams and QA test automation engineers can leverage to develop and ...

It is critical to highlight that machine learning is not a panacea and should be augmented with traditional performance testing and monitoring approaches to achieve the best outcomes.

Princeton researchers applied machine learning methods to develop an optimal policy for ordering common blood tests in a hospital’s intensive care unit. From left: Computer science graduate student ...