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Record W2136805049 · doi:10.1109/iceccs.2004.1310912

Independence transformations and tools for components

2004· article· en· W2136805049 on OpenAlexaff
Denise M. Woit, Min-Hsuan Fan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Reliability and Analysis Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsIndependence (probability theory)Computer scienceComponent (thermodynamics)ContinuationSet (abstract data type)Reliability (semiconductor)Property (philosophy)Composition (language)Work (physics)Programming languageEngineeringMathematics

Abstract

fetched live from OpenAlex

Although component independence is a common underlying assumption in most reliability composition models, relatively little work focuses on this area. Preliminary work, however, shows that continuation passing style (CPS) compliance is an essential property of independent components. We provide a set of transformations which can be used to convert components to functionally equivalent CPS compliant components. We also present a tool to perform these transformations automatically. We include experimental evidence that our tool successfully produces CPS compliant components without altering the functionality of the original components. Use of our tool or manual transformations will aid in the creation of components whose reliabilities can be composed without violating the underlying assumptions of the composition models.

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)0.004
metaresearch head score (Gemma)0.019
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 score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0010.004
Scholarly communication0.0030.006
Open science0.0020.006
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0110.007

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 head0.048
GPT teacher head0.301
Teacher spread0.253 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

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