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Record W2399077472

NDR-Tool: Uma Ferramenta de Apoio ao Reuso de Conhecimento em Requisitos Não Funcionais.

2014· article· pt· W2399077472 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

VenueConferencia Iberoamericana de Software Engineering · 2014
Typearticle
Languagept
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsYork University
Fundersnot available
KeywordsComputer scienceSoftware engineeringSemantics (computer science)Process (computing)Field (mathematics)Requirements elicitationSoftwareProof of conceptProgramming languageRequirements engineering
DOInot available

Abstract

fetched live from OpenAlex

Non-functional requirements (NFR) are fundamental for the software development. The NFRFramework allows the elicitation to deeply cover necessary trade-offs involving synergetic and conflicting solutions. It also favor the capture of design decisions involving the reasons that lead one to choose between one alternative and another to implement a NFR. This work proposes and describes the NDR-Tool, a tool that supports the software engineer in the requirements elicitation and modelling process. This tool proposes the use of ontologies and web semantics techniques to facilitate storing and retrieving knowledge related to possible alternatives to implement NFR. The tool NDRTool was developed and integrated with a tool for modeling NFR diagrams. As proof of concept we used the tool in the medical field.

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)0.003
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
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 score0.327
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.002
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 head0.031
GPT teacher head0.271
Teacher spread0.240 · 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