A semiconductor device includes a semiconductor die having a peripheral region surrounding, a defect detection circuit in the peripheral region, the defect detection circuit arranged in an open conduction loop, the defect detection circuit comprising a plurality of latch circuits and a plurality of defect detection conduction paths, each defect detection conduction path of the plurality of defect detection conduction paths connecting two adjacent latch circuits of the plurality of latch circuits, and a test control circuitry configured to perform (a) a test write operation by transferring bits of an input data pattern in a forward direction of the open conduction loop to cause the plurality of latch circuits to store the bits of the input data pattern in the plurality of latch circuits, and (b) a test read operation by transferring bits stored in the plurality of latch circuits in a backward direction of the open conduction loop.

A method includes associating each block of a plurality of blocks of a memory device with a corresponding frequency access group of a plurality of frequency access groups based on corresponding access frequencies, and performing scan operations on blocks of each of the plurality of frequency access groups using a scan frequency that is different from scan frequencies of other frequency access groups. A scan operation performed on a frequency access group with a higher access frequency uses a higher scan frequency than a scan operation performed on a frequency access group with a lower access frequency.

A method includes associating each block of a plurality of blocks of a memory device with a corresponding frequency access group of a plurality of frequency access groups based on corresponding access frequencies, and performing scan operations on blocks of each of the plurality of frequency access groups using a scan frequency that is different from scan frequencies of other frequency access groups. A scan operation performed on a frequency access group with a higher access frequency uses a higher scan frequency than a scan operation performed on a frequency access group with a lower access frequency.

Data verification technology for ordered event stream (OES) events written into an ordered event stream storage system is disclosed. The verification technology provides perfect reliability. The verification technology further requires low storage overhead in comparison to typical checksums, storing replicated data, etc. Test event data can be generated in a reproducible manner based upon determined OES metadata. OES metadata can be determined from input received via a user interface, via characteristics of an OES storage system, etc., and can be stored for later use in data verification. The test event data can be stored to a portion of an OES storage system under test. The stored test event data can subsequently be verified by using the stored OES metadata to regenerate test event data for comparison to the stored test event data. The test event ordering can be verified via sequence information included in the stored test event data.

Data verification technology for ordered event stream (OES) events written into an ordered event stream storage system is disclosed. The verification technology provides perfect reliability. The verification technology further requires low storage overhead in comparison to typical checksums, storing replicated data, etc. Test event data can be generated in a reproducible manner based upon determined OES metadata. OES metadata can be determined from input received via a user interface, via characteristics of an OES storage system, etc., and can be stored for later use in data verification. The test event data can be stored to a portion of an OES storage system under test. The stored test event data can subsequently be verified by using the stored OES metadata to regenerate test event data for comparison to the stored test event data. The test event ordering can be verified via sequence information included in the stored test event data.

Exemplary methods, apparatuses, and systems include receiving read operations. The read operations are divided into a current set of a sequence of read operations and one or more other sets of sequences of read operations. An aggressor read operation is selected from the current set. A position in the sequence of read operations in the current set is determined such that the position that is preceded by at least a minimum number of read operations following a previous data integrity scan in a previous set of read operations. A data integrity scan is performed on a victim of the aggressor read operation at the determined position in the sequence of the current set of read operations.

Exemplary methods, apparatuses, and systems include receiving read operations. The read operations are divided into a current set of a sequence of read operations and one or more other sets of sequences of read operations. An aggressor read operation is selected from the current set. A position in the sequence of read operations in the current set is determined such that the position that is preceded by at least a minimum number of read operations following a previous data integrity scan in a previous set of read operations. A data integrity scan is performed on a victim of the aggressor read operation at the determined position in the sequence of the current set of read operations.

A memory is provided in which a scan chain covers the redundancy logic for column redundancy as well as the redundancy multiplexers in each column. The redundancy logic includes a plurality of redundancy logic circuits arranged in series. Each redundancy logic circuit corresponds to a respective column in the memory. Each column is configured to route a shift-in signal through its redundancy multiplexers during a scan mode of operation.

A memory is provided in which a scan chain covers the redundancy logic for column redundancy as well as the redundancy multiplexers in each column. The redundancy logic includes a plurality of redundancy logic circuits arranged in series. Each redundancy logic circuit corresponds to a respective column in the memory. Each column is configured to route a shift-in signal through its redundancy multiplexers during a scan mode of operation.

To provide more test data during the manufacture of non-volatile memories and other integrated circuits, machine learning is used to generate virtual test values. Virtual test results are interpolated for one set of tests for devices on which the test is not performed based on correlations with other sets of tests. In one example, machine learning determines a correlation study between bad block values determined at die sort and photo-limited yield (PLY) values determined inline during processing. The correlation can be applied to interpolate virtual inline PLY data for all of the memory dies, allowing for more rapid feedback on the processing parameters for manufacturing the memory dies and making the manufacturing process more efficient and accurate. In another set of embodiments, the machine learning is used to extrapolate limited metrology (e.g., critical dimension) test data to all of the memory die through interpolated virtual metrology data values.