Connectivity today reaches far beyond desktops and smartphones. The Internet of Things (IoT) now powers smart homes, industrial automation, automotive systems, medical devices, and nationwide infrastructure. Yet this expanded digital footprint also widens the attack surface-which in the context of IoT means cyberattacks can escalate into physical consequences.
OpenText, Capgemini and Sogeti have announced the 17th edition of the World Quality Report 2025: Adapting to Emerging Worlds. The report reveals that while nearly 90% of organizations are now actively pursuing generative AI (Gen AI) in their quality engineering (QE) practices, only 15% have achieved enterprise-scale deployment.
Anyone who has ever spent money on a new game or an online casino only to be disappointed knows the value of honest reviews. While professional reviews provide useful technical breakdowns, peer-to-peer insights are becoming increasingly important-especially when combined with beta testing and early access programs.
Every beginner in computer science (CS) hears about software testing sooner or later. Some ignore it, thinking it’s something quality assurance (QA) engineers handle later. Others treat it like a final polish for projects.
When people use an app or website, they expect one simple thing – it should work. Pages should load fast, buttons should respond, and every click should lead where it promises. No one thinks about quality assurance until something breaks. Yet behind every seamless interaction stands a tester who caught the problem before the user did.
Test automation is the backbone of modern software delivery, especially for agile teams striving to release high-quality features at lightning speed. Yet, many Scrum teams struggle to keep automation efficient and adaptable as requirements shift.
In an era where artificial intelligence (AI) writes code, reviews pull requests, and even generates tests, how does the standard Testing Pyramid still hold up? Has it quietly crumbled under more modern demands?
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