Tackling Design Debt With Carefully Considered Design QA

Quality assurance is a vital part of any software development project. QA encompasses the entire software development process from defining goals and commitments to release management and smoke tests. Using different approaches, standards, and models such as ISO 9000 and CMMI, your quality assurance team constantly reviews and audits the software solution you’re developing to verify that it meets the set quality requirements. The team makes certain every feature functions as expected and prevents any deviations or potential errors from making it into the release.

Be that as it may, not every quality assurance procedure gets the same level of attention in the world of fast-paced, iterative software development and delivery practices. Today, tech companies quite often trivialize the role of UX/UI designers in the verification and validation procedures despite design verification being a critical component of the development process. Companies tend to prioritize a faster time to market, putting all the focus on optimizing performance and functionality over polishing the design. This means that while the general acceptance criteria are met, the broader user experience issues — inconsistencies between mockups and the developed UI, possible interaction and navigation deviations, etc. — are usually left unattended or postponed in favor of functionality checks.

How to QA Test Software That Uses AI and Machine Learning

Smartphones, smart speakers, smart cars, smart coffee makers...the list goes on. It seems like everything around us is coming to life and becoming intelligent. And though the sci-fi genre thrives on our ever-present fear of a hostile robot takeover, smart devices are anything but dystopian — they’re actually here to make our lives easier so we can spend more time on the important stuff instead of tedious busywork.

Tech companies know that increased automation is the way of the future, just like it was when Ford pioneered the assembly line. Advanced technology like artificial intelligence (AI) and machine learning (ML) is fueling the most exciting innovations in recent history — think self-driving cars, virtual and augmented reality, automated investing, improved medical imaging, and more. The benefits of this technology are becoming more and more obvious, and companies are rushing toward adoption and racing to build it into their products.