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Record W1979037869 · doi:10.1145/2499777.2499779

Clafer tools for product line engineering

2013· article· en· W1979037869 on OpenAlexaff
Michał Antkiewicz, Kacper Bąk, Alexandr Murashkin, Rafael Olaechea, Liang Jia, Krzysztof Czarnecki

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMetamodelingViewpointsComputer scienceProduct lineFeature modelProduct (mathematics)Software engineeringSoftware product lineModeling languageSystems engineeringSet (abstract data type)Feature (linguistics)New product developmentProduct engineeringEngineering drawingProduct designProgramming languageEngineeringManufacturing engineeringSoftware developmentSoftware

Abstract

fetched live from OpenAlex

Clafer is a lightweight yet expressive language for structural modeling: feature modeling and configuration, class and object modeling, and metamodeling. Clafer Tools is an integrated set of tools based on Clafer. In this paper, we describe some product-line variability modeling scenarios of Clafer Tools from the viewpoints of product-line owner, product-line engineer, and product engineer.

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)0.003
metaresearch head score (Gemma)0.011
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 score0.040
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0030.006
Open science0.0040.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0400.019

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 head0.067
GPT teacher head0.286
Teacher spread0.219 · 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

Citations71
Published2013
Admission routes1
Has abstractyes

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