How predictive analytics will forever change the approach to software testing and QA For the past 3 years, I've been fixated on how to integrate predictive analytics or machine learning to prevent bugs or defects before they are introduced into a software during software development life cycle. Predictive analytics is not new in many product development processes, and is not exactly unheard of for software testing and QA. However recent trend is software testing, and amount of data it provides during various testing phases, gives us more vital data points to utilize in predicting and preventing potential problems before they manifest. The key is monitoring and analysis of vital data points that play important role in avoiding future problems. Power of prediction based on collected data has changed the likes of financial forecasting, medical diagnosis, and insurance industry, and the time is right to deliver higher quality software with fewer defects, while reducing the time QA teams spend in reactive mode, and more in proactive mode. It's a sustainable, reusable process that matures and grows smarter exponentially with each iteration. #SWTesting #QA #AI https://plus.google.com/+ChristopherSaleh/posts/GAbPG4s8FQt?iem=4&gpawv=1&hl=en-US

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