A comprehensive review of memory BIST algorithms for SRAM static fault detection

Aiman Zakwan Jidin, Razaidi Hussin, Mohd Syafiq Mispan, Lee Weng Fook, Loh Wan Ying

Abstract


Memory built-in self-test (MBIST) has become an essential design-for testability technique for ensuring the reliability and quality of embedded memories in modern integrated circuits. The effectiveness of an MBIST implementation is largely determined by its test algorithm, which defines the sequence of memory operations, directly influencing both test complexity and fault coverage. Designing an efficient test algorithm requires balancing low test complexity with comprehensive fault detection. This paper presents a comprehensive review of MBIST test algorithms for static fault detection in static random-access memory (SRAM). The review first summarizes the characteristics of major SRAM static faults and their corresponding detection requirements. It then compares representative test algorithms in terms of test sequence, computational complexity, fault coverage, and design methodology. Furthermore, the evolution of MBIST test algorithm development is discussed, ranging from conventional ad hoc approaches to enhanced algorithms derived from existing March tests. The comparative analysis indicates that an 18N-complexity test algorithm is generally required to achieve complete detection of all unlinked static faults in SRAM, whereas optimized 14N-complexity algorithms provide an effective trade-off between test time and fault coverage. Finally, the review identifies current research challenges, including efficient detection of dynamic and linked memory faults and the development of MBIST algorithms for emerging memory technologies such as magnetic random-access memory (MRAM), highlighting promising directions for future research.

Keywords


March test algorithm; MBIST; Memory fault coverage; SRAM; Static faults

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DOI: http://doi.org/10.11591/ijeecs.v43.i2.pp400-412

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES).

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