STARWEST 2022 - Big Data, Analytics, AI/Machine Learning for Testing
Before You Go!
Don't Miss Special Offers and Program Updates Straight to Your Inbox (Opt-Out at Any Time)!
Tuesday, October 4
A Quality Engineering Introduction to AI and Machine Learning
NewAlthough 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,...
Wednesday, October 5
A Realistic Approach to Scalable and Cost-effective Cross-browser and Device Solution
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...
ML Testing: The Need of a New Way of Thinking
When testing functionality based on Machine learned, or trained functionality, the focus of your testing changes. The code it self stops to be interesting, to some degree, and instead focus need to be elsewhere. Based on personal experience and research projects this talk will highlight the importance of testing your data, why independent testing is vital and how some "old school" tools can help when thinking and planing test activities.
This talk will use trained functionality intended for autonomous driving as base but will also touch more general problems faced when testing...