ALIASING-FREE COMPACTION IN TESTING CORES-BASED SYSTEM-ON-CHIP (SOC) USING COMPATIBILITY OF RESPONSE DATA OUTPUTS
Why this work is in the frame
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Bibliographic record
Abstract
The realization of space-efficient support hardware for built-in self-testing (BIST) is of great importance in the design and manufacture of VLSI circuits. Novel approaches to designing aliasing-free space compaction hardware were recently proposed in the context of testing cores-based system-on-chip (SOC) for single stuck-line faults, extending the well-known concepts of conventional switching theory, specifically those of cover table and frequency ordering commonly utilized in the simplification of switching functions, and of compatibility relation as used in the minimization of incomplete sequential machines, based on optimal generalized sequence mergeability, as developed and utilized by the authors in earlier works. The advantages of these aliasing-free compaction methods over earlier techniques are quite obvious, since zero-aliasing is achieved without any modifications of the module under test (MUT), while keeping the area overhead and signal propagation delay relatively low as contrasted with the conventional parity tree linear compactors. Besides, the approaches could be applied with both deterministic compacted and pseudorandom test patterns. The subject paper, without furnishing details of the different algorithms developed in the implementation of these approaches to designing zero-aliasing space compactors, provides the mathematical basis of selection criteria for merger of an optimal number of outputs of the MUT to achieve maximum compaction ratio in the design, along with some results from simulation experiments conducted on ISCAS 85 combinational and ISCAS 89 full-scan sequential benchmark circuits, with simulation programs ATALANTA, FSIM, and HOPE.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it