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Record W2103145766 · doi:10.1109/iccd.1992.276264

BIST generators for sequential faults

2003· article· en· W2103145766 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVLSI and Analog Circuit Testing
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsBenchmark (surveying)Linear feedback shift registerGenerator (circuit theory)Cellular automatonComputer scienceShift registerAlgorithmSequential logicAutomatic test pattern generationBuilt-in self-testAutomatonElectronic circuitState (computer science)MathematicsTheoretical computer scienceLogic gateEngineeringEmbedded systemPower (physics)

Abstract

fetched live from OpenAlex

The authors consider faults with sequential behavior, e.g., delay or stuck-open faults, and discuss the state transition properties of linear-feedback-shift-register (LFSR) and one-dimensional linear-hybrid-cellular-automata (LHCA) test pattern generators. Upper and lower bounds on the transition coverage of any general n-cell generator with a period of 2/sup n/-1 are presented. It is shown that an XLHCA/XLFSR test pattern generator, which is derived from an LHCA/LFSR by grouping the odd and even numbered cell outputs, has superior transition coverage. On the basis of analysis and results of simulating the ISCAS'85 benchmark circuits, it is concluded that the XLHCA and XLFSR are excellent candidates for test pattern generators in BIST to detect faults with sequential behavior.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score0.208

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 science0.0000.000
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 head0.036
GPT teacher head0.262
Teacher spread0.226 · 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

Quick stats

Citations25
Published2003
Admission routes1
Has abstractyes

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