Machine-learning-based design-for-test (DFT) recommendation system for improving automatic test pattern generation (ATPG) quality of results (QOR)

US11829692B1 · kind B1 · utility

Assignee

• SYNOPSYS, INC. · US

Inventors

• Apik A. Zorian · Santa Clara, US
• Fadi Maamari · Mountain View, US
• Suryanarayana Duggirala · San Jose, US
• Mahilchi Milir Vaseekar Kumar · San Jose, US
• Basim Mohammed Issa Shanyour · Carbondale, US

Key dates

• Filing date: Jun 11, 2021
• Grant date: Nov 28, 2023
• Expiry date: Sep 21, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G01R31/318536
• WIPO field: Measurement
• WIPO sector: Instruments

Abstract

Training data may be collected based on a set of test-case configurations for each integrated circuit (IC) design in a set of IC designs. The training data may include a set of features extracted from each IC design, and a count of test cycles required for achieving a target test coverage for each test-case configuration. A machine learning (ML) model may be trained using the training data to obtain a trained ML model. The trained ML model may be used to predict a set of ranked test-case configurations for a given IC design based on features extracted from the given IC design.