Title: A Comprehensive Data-Driven Function Verification Process

Speaker: Tsungyu Tsai, Siemens

As Machine Learning (ML) technology is all the rage these years, data collection has become one of the keys to daily work. The increasingly complex designs will no longer be a problem with the help of ML technology. We can apply ML technology on getting the scenarios/checkers that mapping to the test-plan, testcase analysis, coverage closure, prediction or identification of error causes, and presentation of verification results. In order to have enough big data for ML to obtain accurate inferences, a complete process for function verification becomes crucial. In this paper, we propose a complete process that includes each stage of function verification and a method of collecting relevant data. By applying this process, the collected data can be perfectly applied to various applications. And this process is compatible with different verification methods, including dynamic simulation and static analysis.