Signature-Based Testing for Digitally-Assisted Adaptive Equalizers in High-Speed Serial Links

An automatic test generation framework for digitally-assisted adaptive equalizers in high-speed serial links

“…Figure 6 shows the fitness vs. generation during the GA process for two exemplar faults. In comparison, we also mark the fitness values of the manual tests (denoted as HM -standing for hand-made) which were used in [10]. As the manual stimulus does not evolve and the iteration count is irrelevant to its fitness, its fitness is therefore marked as a horizontal dashed line in this fitness-vs-iteration plot.…”

“…In this work, we use a further enhanced dynamic signature over the previous work in [10]. The tap coefficients' convergence characteristics of the DUT are sampled over a specific range during the adaptation process.…”

“…However, due to the limited types of test stimuli applied and only very limited information extracted from the observed tap coefficients, there exist hard-to-detect faults that cannot be covered by this method. In [10], an enhancement is proposed, which captures signatures from the sequences of tapcoefficient values during adaptation for fault detection. These captured signatures are referred to as 'dynamic signatures'.…”

“…These captured signatures are referred to as 'dynamic signatures'. The effectiveness of using the dynamic signatures for detecting the hard-to-detect faults was successfully demonstrated in [10]. However, the test stimuli used for signature generation was selected based on manual trials.…”

“…In [10] different test stimuli are used to enhance the fault coverage of the static signatures and further proposed the use of dynamic signatures for fault detection. Dynamic signatures are derived by integrating the DUT's tap coefficients over a selected range of iterations during the adaptation process.…”