Random Pattern Testability Enhancement by Circuit Rewiring
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Generally, there exist random‐pattern resistant faults that result in the poor fault coverage in Build‐In Self‐Testing (BIST) scheme. In this paper, we propose a method to enhance the random pattern testability by a circuit restructuring technique, called circuit rewiring . The basic idea of rewiring is to replace a wire by another wire with the circuit functionality remaining unchanged. For two types of rewiring, fanin rewiring and fanout rewiring, we first analyze the testability change for each type of wire replacement. Based on the analysis, an efficient algorithm is given to enhance circuit testability. For a poor observability node, we try to increase its observability by adding an additional fanout to the node and removing an alternative wire whose source node has relatively good observability. The technique does not introduce any hardware overhead and performance degradation since a wire addition is followed immediately by another wire removal. Thus, it is basically cost‐free when compared to other testability enhancement techniques.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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