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Record W2138422843 · doi:10.1109/csmr.2007.8

A Multi-view Toolkit to Assist Software Integration and Evolution

2007· article· en· W2138422843 on OpenAlexaff
Kamran Sartipi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSoftware product lineSoftware engineeringComputer scienceDomain engineeringCohesion (chemistry)Systems engineeringReuseComponent-based software engineeringReference architectureComponent (thermodynamics)Software evolutionSoftware systemSoftware developmentSoftware architectureSoftwareSoftware constructionEngineeringProgramming language

Abstract

fetched live from OpenAlex

Software product line engineering aims at producing functionally similar software systems as a family of products. In this process, the development life cycle has been shifted from traditional activities into reuse-centric and customizable component approaches. In software product line engineering from existing systems many technical, organizational, and user-adoption problems need to be dealt with by the means of proper tool support. In this context, we provide a supporting toolkit that blends the behavior and structure recovery techniques in order to localize the major components of the existing systems as candidates for generic or reusable components. An integration of the reusable and new components will form a domain reference architecture, whose instantiation will produce the products. For each new product the scattering of the added features in the structure of the original components will be determined by the means of two metrics to assess the functional cohesion and feature functional scattering. This allows us to control the structural evolution of the product line engineering process

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 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.957
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.046
GPT teacher head0.319
Teacher spread0.273 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2007
Admission routes1
Has abstractyes

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