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Record W1938620772 · doi:10.1109/iccd.1996.563529

Design for testability of integrated operational amplifiers using oscillation-test strategy

2002· article· en· W1938620772 on OpenAlexaff
K. Arabi, Bożena Kamińska, Stephen Sunter

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicVLSI and Analog Circuit Testing
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsOscillation (cell signaling)TestabilityDesign for testingElectronic engineeringComputer scienceOverhead (engineering)AmplifierAutomatic test pattern generationOperational amplifierControl theory (sociology)Reliability engineeringEngineeringElectrical engineeringElectronic circuitCMOS

Abstract

fetched live from OpenAlex

This paper treats the problem of testing integrated operational amplifiers. The efficiency of a new low-cost vector-less test solution, known as oscillation-test, is investigated. During the test mode, the op-amps are converted to a circuit that oscillates. The oscillation frequency is evaluated to monitor faults. The tolerance band of the oscillation frequency is determined using a Monte Carlo analysis taking into account the nominal tolerance of all important technology and design parameters. Faults in the op-amps under test which cause the oscillation frequency to exit the tolerance band can therefore be detected. Some design for testability (DFT) rules to rearrange op-amps to form oscillators are presented and the related practical problems and limitations are discussed. The oscillation frequency can be easily and precisely evaluated using pure digital circuitry. The simulation and practical implementation results confirm that the presented method assures a high fault coverage with a low area overhead.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.137
GPT teacher head0.286
Teacher spread0.148 · 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 designBench or experimental
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

Citations23
Published2002
Admission routes1
Has abstractyes

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