STARWEST 2022 - Big Data, Analytics, AI/Machine Learning for Testing

Although there are several controversies and misunderstandings surrounding AI and machine learning, one thing is apparent — people have quality concerns about the safety, reliability, and trustworthiness of these types of systems. Not only are ML-based systems shrouded in mystery due to their largely black-box nature, they also tend to be unpredictable since they can adapt and learn new things at runtime. Validating ML systems is challenging and requires a cross-section of knowledge, skills, and experience from areas such as mathematics, data science, software engineering, cyber-security,...

Problem Statement: Current cross browser/device platforms are not built to handle the real scalability that software development design patterns require, in a cost-efficient way.

Most or all cross-browser platforms offer their services based on the number of parallel connections. The more connections you need, the more expensive it gets. Here you must choose quality vs cost. With the current providers, without spending in millions, you would not be able to implement shift left with full scalability. This is because the current platforms are not aligned to the best practices of CI CD...