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Record W4214647708 · doi:10.1002/smr.377

Search‐based many‐to‐one component substitution

2008· article· en· W4214647708 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

VenueJournal of Software Maintenance and Evolution Research and Practice · 2008
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsComponent (thermodynamics)Substitution (logic)UnavailabilityComputer scienceMechanism (biology)HeuristicsObsolescenceEngineeringReliability engineeringProgramming language

Abstract

fetched live from OpenAlex

Abstract In this paper, we present a search‐based automatic many‐to‐one component substitution mechanism. When a component is removed from an assembly to overcome component obsolescence, failure or unavailability, most existing systems perform component‐to‐component (one‐to‐one) substitution. Thus, they only handle situations where a specific candidate component is available. As this is not the most frequent case, it would be more flexible to allow a single component to be replaced by a whole component assembly (many‐to‐one component substitution). We propose such an automatic substitution mechanism, which does not require the possible changes to be anticipated and which preserves the quality of the assembly. This mechanism requires components to be enhanced with ports, which provide synthetic information on components' assembling capabilities. Such port‐enhanced components then constitute input data for a search‐based mechanism that looks for possible assemblies using various heuristics to tame complexity. Copyright © 2008 John Wiley & Sons, Ltd.

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)0.006
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.564
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.153
GPT teacher head0.379
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