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Record W2116295136 · doi:10.1109/metric.2003.1232451

Metrology, measurement and metrics in software engineering

2004· article· en· W2116295136 on OpenAlex
Alain Abran, Asma Sellami, Witold Suryn

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
TopicSoftware Engineering Research
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsSoftware measurementMetrologyComputer scienceSoftwareSoftware engineeringDomain (mathematical analysis)Software developmentSoftware Engineering Process GroupPosition paperSocial software engineeringSystems engineeringPerspective (graphical)Software constructionEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Up until recently software 'metrics' have been most often proposed as the quantitative tools of choice in software engineering, and the analysis of these had been most often discussed from the perspective referred to as 'measurement theory'. However, in other disciplines, it is the domain of knowledge referred to as 'metrology' that is the foundation for the development and use of measurement instruments and measurement processes. The IEEE-computer society, with the support of a consortium of industrial sponsors, has recently published a guide to the Software Engineering Body of Knowledge (SWEBOK) and, throughout this guide, measurement is pervasive as a fundamental engineering tool. We use our initial modelling of the sets of measurement concepts documented in the ISO international vocabulary of basic and general terms in metrology to investigate and position the measurement concepts within this body of knowledge, and to identify gaps where further research on software measurement is required.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.680
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.027
GPT teacher head0.238
Teacher spread0.211 · 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

Quick stats

Citations39
Published2004
Admission routes1
Has abstractyes

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