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Record W1516086305

Measurement model of software requirements derived from system maintainability requirements

2010· article· en· W1516086305 on OpenAlexaff
Alain Abran, Khalid T. Al‐Sarayreh, Juan J. Cuadrado‐Gallego

Bibliographic record

VenueSoftware Engineering and Knowledge Engineering · 2010
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsMaintainabilityFunctional requirementReliability engineeringSoftware requirements specificationSoftwareSystems engineeringComputer scienceSoftware systemSoftware requirementsSoftware engineeringRequirements analysisSystem requirementsSoftware constructionEngineeringOperating system
DOInot available

Abstract

fetched live from OpenAlex

Maintainability is typically described initially as a non functional requirement at the system level. Systems engineers must subsequently apportion these system requirements very carefully as either software or hardware requirements to conform to the maintainability requirements of the system. A number of concepts are provided in the ECSS, ISO 9126, and IEEE standards to describe the various types of candidate maintainability requirements at the system, software, and hardware levels. This paper organizes these concepts into a generic standards-based reference model of the requirements at the software level for system maintainability. The structure of this reference model is based on the generic model of software requirements proposed in the COSMIC – ISO 19761 model, thereby allowing the measurement of the functional size of such maintainability requirements implemented through software. Keywords—Maintainability Requirements, Non functional requirements – NFR, Functional size, COSMIC – ISO 19761, ECSS International Standards, Software Maintainability Measurement.

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)0.005
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.041
GPT teacher head0.263
Teacher spread0.221 · 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 designSimulation or modeling
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

Citations7
Published2010
Admission routes1
Has abstractyes

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