The days of large blanket media buys are fading. Always-on testing reduces waste by directing spend toward what is proven to ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Abstract: Exponential growth of unstructured data in the form of text documents, emails, and web content presents a noticeable challenge to automated data extraction. This kind of data has much more ...

The adoption of automation in software testing presents challenges that can hinder its effectiveness and scalability. This study systematically investigates these challenges using a multi-phase ...