MétaCan
Menu
Back to cohort
Record W2184943467

Formal Model Driven Approach to Deal with Requirements Volatility

2008· article· en· W2184943467 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsComputer scienceTupleModel transformationTransformation (genetics)Requirements engineeringConsistency (knowledge bases)Requirements elicitationRelational modelFeature modelRequirements analysisTheoretical computer scienceAlgebra over a fieldSoftwareRelational databaseMathematicsProgramming languageData miningArtificial intelligenceDiscrete mathematicsPure mathematics
DOInot available

Abstract

fetched live from OpenAlex

To deal with software requirements volatility, we present a model transformation of a software family requirements model into detailed requirements models of its members. This transformation is based on feature algebra and relation algebra. We give the mathematical foundation for this transformation system. The initial models are the result of engineering requirements processes. In other terms, they are the result of elicitation and formalization activities. A family model is represented by a feature algebra term. The features of the family are requirements scenarios formalized into relational scenarios, which are 2-tuples of relations. Throughout the transformation of the initial models into the detailed models, the consistency of the specified system as well as that of its environment are verified.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.260
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.112
GPT teacher head0.296
Teacher spread0.184 · 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