Organizations that implement continuous testing within Agile and DevOps execute a large variety of testing types multiple times a day. With each test execution, the amount of test data that’s being created grows significantly, making the decision-making process harder.
With AI and machine learning, executives should be able to better slice and dice test data, understand trends and patterns, quantify business risks, and make decisions faster and continuously. Without the help of AI or machine learning, the work is error-prone, manual and sometimes impossible.
WHAT YOU'LL LEARN
- How machine learning helps make sense of extremely high quantities of test data
- Use machine learning to make actionable decisions around quality for releases
- How machine learning can enhance test stability over time
Applause is the worldwide leader in crowdsourced digital quality testing. With testers available on-demand around the globe, Applause provides brands with a full suite of testing and feedback capabilities. This approach drastically improves testing coverage, eliminates the limitations of offshoring and traditional QA labs, and speeds up time-to-market.