Novel March Test Algorithm Optimization Strategy for Improving Unlinked Faults Detection

• Published in: 2021 IEEE Asia Pacific Conference on Circuit and Systems (APCCAS) pp. 117 - 120
• Main Authors: Jidin, Aiman Zakwan, Hussin, Razaidi, Mispan, Mohd Syafiq, Fook, Lee Weng
• Format: Conference Proceeding
• Language: English
• Published: IEEE 22-11-2021
• Subjects: Automation; Circuits and systems; Complexity theory; Conferences; Electrical fault detection; Fault detection; March Test Algorithm; Memory BIST; Memory Fault Detection Optimization; Memory Fault Models; Performance analysis; Random Access Memory
• DOI: 10.1109/APCCAS51387.2021.9687791

March-series test algorithms have proven to be popular choices for Memory BIST implementation, owing to their simplicity yet having a good fault coverage. However, March test algorithms with low test complexities are incapable to detect some unlinked static Single-Cell faults and many Double-Cell faults. This paper presents a new optimization strategy to improve the fault coverage of the existing March algorithms by detecting the previously undetectable Single-Cell faults and Double-Cell faults. It is achieved by optimizing the test operation sequences of the existing March test algorithms through an automation program, to achieve higher fault coverage while maintaining the same test complexity as the original March algorithm. Performance analysis shows that the fault coverage of March LR and March SR algorithms can be improved from 44% to 72% and from 61% to 69%, respectively, by using the proposed optimization strategy.