  The academic community has made outstanding achievements in researching the
March algorithm. However, the current fault modeling method, which centers on
fault primitives, cannot be directly applied to analyzing the March algorithm.
This paper proposes a new test primitive. The test primitives, which decouple
the cell states from sensitization and detection operations, describe the
common features that must be possessed for the March algorithm to detect
corresponding faults, forming a highly flexible and scalable March algorithm
analysis unit. The theoretical analysis proves that the test primitives
demonstrate completeness, uniqueness, and conciseness. On this foundation, the
utilization of test primitives within the March analysis procedure is
elucidated.
