The majority of software development teams believe they don’t test well. They understand that the effect of quality defects is substantial, and they invest heavily in quality assurance, but they still aren’t getting the results they want. This is not due to a lack of talent or effort — the technology supporting software testing is simply not effective. The industry has been underserved.
There can’t be a successful release until software has been properly and thoroughly tested, and testing can sometimes take significant resources considering the amount of time and human effort required to get the job done right. This gaping need is just beginning to be filled.
Machine learning (ML), which has disrupted and improved so many industries, is just starting to make its way into software testing. Heads are turning, and for good reason: the industry is never going to be the same again. While machine learning is