MétaCan
Menu
Back to cohort
Record W2259658967

Analysis of the ISO 9126 on software product quality evaluation from the metrology and ISO 15939 perspectives

2006· article· en· W2259658967 on OpenAlexaff
Alain Abran, Rafa E. Al-Qutaish, Juan J. Cuadrado‐Gallego

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsMetrologySoftwareSoftware measurementDocumentationSystems engineeringVerification and validationSoftware qualityEngineeringQuality assuranceSoftware engineeringComputer scienceReliability engineeringSoftware developmentMathematicsOperations managementStatisticsProgramming language
DOInot available

Abstract

fetched live from OpenAlex

Abstract:- While metrology has a long tradition of use in physics and chemistry, it is rarely referred to in the software engineering measurement, and in particular, in the design and documentation of software measures. Using the ISO 9126-4 Technical Report on the measurement of software quality in use as a case study, this paper reports on the extent to which this ISO series addresses the metrology criteria typical of classic measurement. Areas for improvement in the design and documentation of measures proposed in ISO 9126-4 are

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)0.064
metaresearch head score (Gemma)0.088
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.337

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0640.088
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0250.018
Science and technology studies0.0020.004
Scholarly communication0.0090.006
Open science0.0020.003
Research integrity0.0020.002
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 head0.031
GPT teacher head0.323
Teacher spread0.292 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations8
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicSoftware Engineering ResearchFrench-language works237,207