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Record W2131934454 · doi:10.1109/vtest.1995.512651

On the design of at-speed testable VLSI circuits

2002· article· en· W2131934454 on OpenAlexaff
M. Soufi, Yvon Savaria, Bożena Kamińska

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVLSI and Analog Circuit Testing
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsObservabilityTestabilityDesign for testingComputer scienceVery-large-scale integrationAutomatic test pattern generationTest compressionElectronic circuitScan chainSpeedupFault coverageElectronic engineeringBenchmark (surveying)Integrated circuitReliability engineeringParallel computingEmbedded systemEngineeringElectrical engineeringMathematics

Abstract

fetched live from OpenAlex

In this paper, a new design-for-testability technique for sequential circuits is presented. This technique may be considered as an alternative to full scan. The fault coverages obtained with this technique are comparable to those produced by full scan techniques. However, the present method improves full scan in several ways. The application test time of a device is reduced to that of applying parallel vectors at the operational speed. This characteristic of applying test vectors at the operational speed has a positive impact on the test quality. Indeed, a stuck-at test, applied at the operational speed of the circuit, identifies more defective chips than the same test applied at a lower speed. Furthermore, the timing and the area overheads, which are often considered to be serious disadvantages of DFT techniques, are in this case acceptable. With this method, all FFs are replaced with XFF gates. The XFF gate is similar to a T flip-flop without feedback. However, in some cases, when observability problems are still important, a probe observation point is inserted at the pseudo-primary inputs (PPIs).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.083
GPT teacher head0.219
Teacher spread0.137 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

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