Narrow Results

Conventional march memory tests have high fault coverage, especially for simple faults like stack-at fault (SAF), transition fault (TF) or coupling fault (CF). The same-time standard march tests, which are based on only one run, are becoming insufficient for complex faults like pattern-sensitive faults (PSFs). To increase fault coverage, the multi-run transparent march test algorithms have been used. This solution is especially suitable for built-in self-test (BIST) implementation. The transparent BIST approach presents the incomparable advantage of preserving the content of the random access memory (RAM) after testing. We do not need to save the memory content before the test session or to restore it at the end of the session. Therefore, these techniques are widely used in critical applications (medical electronics, railway control, avionics, telecommunications, etc.) for periodic testing in the field. Unfortunately, in many cases, there is very limited time for such test sessions. Taking into account the above limitations, we focus on short, two-run march test procedures based on counter address sequences. The advantage of this paper is that it defines requirements that must be taken into account in the address sequence selection process and presents a deeply analytical investigation of the optimal address decimation parameter. From the experiments we can conclude that the fault coverage of the test sessions generated according to the described method is higher than in the case of pseudorandom address sequences. Moreover, the benefit of this solution seems to be low hardware overhead in implementation of an address generator.

Simultaneous tests of a huge number of hypotheses is a core issue in high flow experimental methods. In the central debate about the type I error rate, [Benjamini and Hochberg, 1995] have provided a procedure that controls the now popular False Discovery Rate (FDR).

The present paper focuses on the type II error rate. The proposed strategy improves the power by means of moderated test statistics integrating external information available in a double-sampling scheme. The small sample distribution of the test statistics is provided. Finally, the present method is implemented on transcriptomic data.