Part 1 of this two-part blog serves as the foundation, highlighting the critical role that quality engineering (QE) must play in addressing the business risks associated with the accelerating adoption of artificial intelligence or AI-powered software.
From social media and Google reviews to sensors and artificial intelligence (AI) assistants, development teams today have access to so much user data, often called big data, that it sometimes feels like a blessing and a curse.
According to Stack Overflow’s recent survey, 62% of developers share a common concern – a growing and never-ending technical debt.
Mobile apps are the key to business success, accounting for a quarter of companies’ revenue, according to Kobiton research. However, 75% of companies report that slow app releases cost them…
Accessibility is important to all users of digital products as it helps them use the product without becoming disabled by code that doesn’t consider accessibility requirements. More people are becoming…
The perfect defect-free app doesn’t exist… unless you shrink your codebase and deliver a product no one wants to use. Even then, there’s no guarantee it won’t have issues. For…
“Sorry, we couldn’t process your payment. Please try again.” It’s probably the most frustrating issue customers encounter. After all, they took the time to search for a product they wanted…
Legacy enterprises can often resist software testing modernization. An established brand presence and loyal customer base intensify the pressure to introduce new features and technology and can act as barriers…