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Record W2179793844

gRUP- A Globalized Approach to Software Engineering.

2008· article· en· W2179793844 on OpenAlexaff
Amr El-Kadi, Omar Badreddin

Bibliographic record

VenueSoftware Engineering and Data Engineering · 2008
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGlobalizationRational Unified ProcessInternationalizationComputer scienceProcess (computing)SoftwareScheduleSoftware engineeringSoftware development processSoftware qualitySoftware developmentProcess managementSystems engineeringEngineeringBusinessEconomicsInternational trade
DOInot available

Abstract

fetched live from OpenAlex

This research has the main objective of enhancing the Rational Unified Process to better address the emerging new Globalization and Internationalization requirements of modern software, focusing on integrating the Globalization Processes, Artifacts, Roles, Activities, and best practices into the Rational Unified Process (RUP). RUP is a well established Software Development Process (SDP) that intends to guarantee quality by controlling the project schedule, budget, communication, productivity, and trustworthiness. Meanwhile, the gRUP - produced in the coarse of this research - intends to guarantee that the developed software is ready for globalization, matches the required globalization and internationalization requirements, and ensures the implementation of best practices and tests to guarantee that the produced software is globalization ready. gRUP is constructed by incorporating essential globalization activities and artifacts into RUP, and incorporates an additional Globalization Discipline to the standard nine RUP disciplines.

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)0.006
metaresearch head score (Gemma)0.006
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 score0.007
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.005
Scholarly communication0.0070.006
Open science0.0010.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.002

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 head0.030
GPT teacher head0.246
Teacher spread0.216 · 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
Published2008
Admission routes1
Has abstractyes

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