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Record W113659863

Towards a Knowledge-Based Representation of Non-Functional Requirements

2012· article· en· W113659863 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

VenueInternational Conference on Software Engineering Advances · 2012
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsComputer scienceOntologyNon-functional requirementSemantics (computer science)Representation (politics)Knowledge representation and reasoningDomain (mathematical analysis)Functional requirementSoftware engineeringKnowledge managementArtificial intelligenceProgramming languageSoftware developmentSoftwareMathematics
DOInot available

Abstract

fetched live from OpenAlex

Knowledge-based representation is necessary to support the description of Non-Functional Requirements within a system and to provide practitioners and researchers with a valuable alternative to current requirements engineering techniques. The aim of our research reported in this paper is to systematically develop an ontology which provides the definition of the general concepts relevant to NFRs without reference to any particular application domain. The general concepts can then act as a common foundation for describing particular non-functional attributes as well as providing a conceptual model for NFRs (including, e.g., entity definitions, relations, etc.). The ontology also contains rules which define the semantics of the defined concepts.

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)0.002
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 score0.493
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.103
GPT teacher head0.367
Teacher spread0.264 · 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