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Record W2075105459 · doi:10.1049/ip-cdt:20045019

Resource-constrained system-on-a-chip test: a survey

2005· article· en· W2075105459 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

VenueIEE Proceedings - Computers and Digital Techniques · 2005
Typearticle
Languageen
FieldComputer Science
TopicVLSI and Analog Circuit Testing
Canadian institutionsMcMaster University
Fundersnot available
KeywordsReuseTest (biology)Computer scienceTest Management ApproachResource (disambiguation)Key (lock)Embedded systemEngineeringOperating system

Abstract

fetched live from OpenAlex

Manufacturing test is a key step in the implementation flow of modern integrated electronic products. It certifies the product quality, accelerates yield learning and influences the final cost of the device. With the ongoing shift towards the core-based system-on-a-chip (SOC) design paradigm, unique test challenges, such as test access and test reuse, are confronted. In addition, when addressing these new challenges, the SOC designers must consciously use the resources at hand, while keeping the testing time and volume of test data under control. Consequently, numerous test strategies and algorithms in test architecture design and optimisation, test scheduling and test resource partitioning have emerged to tackle the resource-constrained core-based SOC test. This paper presents a survey of the recent advances in this field.

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 categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score1.000

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 communication0.0020.001
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 head0.017
GPT teacher head0.224
Teacher spread0.206 · 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