This tutorial will cover the evolution of features and tools to provide efficiency and acceleration to the verification process as well as the revolution required to take full advantage of collaboration, traceability, and emerging technologies provided by machine learning (ML) and virtually unlimited cloud computing resources.
What you will learn:
- How to enhance your current D&V workflow with proven collaboration, requirements traceability, coverage tracking, regression management, and more as inspired by proven technologies from the software world
- How verification planning tools can be integrated with lifecycle management flows by taking advantage of the Open Services for Lifecycle Collaboration standard.
- How ML can be applied to the analysis of the coverage model using analytical navigation to speed understanding and accelerate closure, how ML can complement rules-based systems to improve regression efficiency and debug turn-around times, and how this enables a shift from descriptive to prescriptive analytics with full visibility of the status of projects
- What is required to take full advantage of this kind of massive compute resource scalability with respect to both dynamic reaction and streaming data.
Darron May, Mark Carey, Dan Yu, Joseph Hupcey