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Record W1575720719 · doi:10.1109/ats.1992.224449

Cyclogen: automatic, functional-level test generator

2003· article· en· W1575720719 on OpenAlexaff
B. Ayari, Bożena Kamińska

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVLSI and Analog Circuit Testing
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsBinary decision diagramBoolean functionCyclomatic complexityComputer scienceGenerator (circuit theory)Benchmark (surveying)Representation (politics)Theoretical computer scienceAlgorithmBoolean circuitProgramming languageSoftware

Abstract

fetched live from OpenAlex

The authors have laid the foundations for a functional test generation procedure based on a cyclomatic complexity measure (CCM) and on the reduced, ordered binary decision diagram representation (ROBDD) for Boolean function manipulation. The CCM has been defined for one-output and multi-output electronic circuits predicting a minimal number of test vectors. This new test generation approach, called Cyclogen, has been implemented, and the tests for several functional primitives as well as for the ISCAS-85 benchmark circuits have been generated successfully. The results show that this approach is effective and promising.>

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.047
GPT teacher head0.225
Teacher spread0.178 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations7
Published2003
Admission routes1
Has abstractyes

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