Fault Detection with Optimum March Test Algorithm

Zakaria, Nor Azura; Hasan, Wan Zuha Wan; Halin, Izhal Abdul; Sidek, Roslina Mohd; Wen, Xiaoqing

doi:10.1109/isms.2012.88

Cited by 9 publications

(11 citation statements)

References 12 publications

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“…Moreover, in many cases, the sensitization of the victim cell must consider all possible values of the aggressor cell (logic 0 and 1). Therefore, it can be said that there are 8 possible cases for each of the CFtr, CFrd, CFdrd, and CFwd [25], [38], [39].…”

Section: Memory Functional Fault Modelsmentioning

confidence: 99%

“…An improvement was proposed in [25] by developing an automation program that can optimize the test operation of the existing March test algorithms, by having a set of test sequence generation rule schemes. This research managed proposes March CL-1 algorithm (⇕(w0); ⇑(r0, w0); ⇑(r0); ⇑(r0, w1); ⇓(r1, w1); ⇕(r1); ⇓(r1, w0); ⇕(r0)) and March-SR1 algorithm (⇕(w0); ⇑(r0, w0, r0, w1); ⇑(r1, r1); ⇑(w1); ⇓(r1, w0, r0, w0); ⇓(r0, w0)), as the results of March CL and March SR algorithm optimization.…”

Section: Previous Work On Improving the Memory Testing Algorithmsmentioning

confidence: 99%

“…In contrast, some research focus only on reducing the test complexity of the existing algorithm and does not offer any improvement on the fault coverage [7], [11]. While some research work like the one proposed by The research proposed in [25] managed to optimized the March SR algorithm to improve its fault coverage while maintaining the same test complexity. However, some weaknesses were identified in this research.…”

Section: Previous Work On Improving the Memory Testing Algorithmsmentioning

confidence: 99%

“…As the number of possible faults can be unlimited [24], this paper focuses on the commonly used fault models in the literature. This paper also discusses different memory test algorithms with a focus on March series test algorithms as they are commonly used in the industry due to their simplicity, linear-time test complexity, and low area overhead [25]- [27]. The notations used for describing the fault models and the test algorithms are also presented.…”

Section: Introductionmentioning

confidence: 99%

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A review paper on memory fault models and test algorithms

Jidin

Hussin

Fook³

et al. 2021

Bulletin EEI

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Testing embedded memories in a chip can be very challenging due to their high-density nature and manufactured using very deep submicron (VDSM) technologies. In this review paper, functional fault models which may exist in the memory are described, in terms of their definition and detection requirement. Several memory testing algorithms that are used in memory built-in self-test (BIST) are discussed, in terms of test operation sequences, fault detection ability, and also test complexity. From the studies, it shows that tests with 22 N of complexity such as March SS and March AB are needed to detect all static unlinked or simple faults within the memory cells. The N in the algorithm complexity refers to Nx*Ny*Nz whereby Nx represents the number of rows, Ny represents the number of columns and Nz represents the number of banks. This paper also looks into optimization and further improvement that can be achieved on existing March test algorithms to increase the fault coverage or to reduce the test complexity.

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Section: Memory Functional Fault Modelsmentioning

confidence: 99%

Section: Previous Work On Improving the Memory Testing Algorithmsmentioning

confidence: 99%

Section: Previous Work On Improving the Memory Testing Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A review paper on memory fault models and test algorithms

Jidin

Hussin

Fook³

et al. 2021

Bulletin EEI

View full text Add to dashboard Cite

show abstract

“…Developments and improvements in the algorithms of memory testing have made the simultaneous announcement of several faults possible. The announced fault from BIST to the BISR circuit for WOMs is in the form of (R, W, Fail_Word) [3] where R, W and Fail_Word (FW) respectively represent row address, Word address and a string of binary which extracted by MARCH algorithm [4].…”

Section: Introductionmentioning

confidence: 99%