Smart Sampling for Efficient System Level Test: A Robust Machine Learning Approach

System level tests (SLTs) are important and expensive procedures to ensure high quality of IC products. In the volume production stage with stable yield, efforts such as random sampling have been made to improve testing efficiency. However random sampling doesn’t fully utilize information gathered before SLT and is not optimal. In this paper we propose both supervised (SVM) and unsupervised (AutoE...