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Record W2404250845

Non-functional Properties in Software Product Lines: A Taxonomy for Classification.

2012· article· en· W2404250845 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

VenueSoftware Engineering and Knowledge Engineering · 2012
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsAthabasca UniversityUniversity of New Brunswick
Fundersnot available
KeywordsComputer scienceSoftware product lineSoftware developmentSoftware quality controlSoftware qualitySoftware engineeringSoftwareTaxonomy (biology)Product (mathematics)Quality (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

In the recent years, the software product lines paradigm has gained interest in both industry and academia. As in traditional software development, the concept of quality is crucial for the success of software product line practices and both functional and nonfunctional characteristics must be involved in the development process in order to achieve a high quality software product line. Therefore, many efforts have been made towards the development of quality-based approaches in order to address non-functional properties in software product line development. In this paper, we propose a taxonomy that characterizes and classifies various approaches for employing non-functional properties in software product lines development. The taxonomy not only highlights the major concerns that need to be addressed in the area of quality-based software product lines, but also helps to identify various research gaps that need to be filled in future work in this area.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.270
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.078
GPT teacher head0.258
Teacher spread0.180 · 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