As a consumer, when you think of Red Bull, it’s impossible not to recognize how deeply the brand’s reputation is tied to exceptional experiences.
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.
The quality assurance (QA) process is vital for creating dependable and efficient software. It ensures that defects or issues are identified early in the development lifecycle. This guarantees that the…
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.
Managing issue tracking across teams can be straightforward with centralized platforms like GitHub or BitBucket. But what happens when your testing needs go beyond basic coordination?
Testing in production involves evaluating software directly in a live environment as real users. It’s becoming increasingly common.
Imagine your app faces a sudden surge in users. Thousands log in at once. Can your system handle the pressure, or will it crash?
The global software testing market is expected to surpass $60 billion in 2023. This fact underscores the growing importance of quality assurance (QA) in software development.