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Record W1879993036 · doi:10.1109/sess.1999.766599

A structured analysis of the new ISO standard on functional size measurement-definition of concepts

2003· article· en· W1879993036 on OpenAlexafffund
Alain Abran, J. Jacquet

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStandardizationStrengths and weaknessesComputer scienceCompleteness (order theory)Process (computing)SoftwareSoftware engineeringSet (abstract data type)Software measurementPerspective (graphical)Contrast (vision)Systems engineeringData miningSoftware qualitySoftware developmentEngineeringMathematicsArtificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

The ISO 14143-1 document is the first in a set of five documents constituting the international standard on functional size measurement for software. This first document specifies a mandatory set of concepts required for functional size measurement and tackles it from a measurement method perspective. This is a unique perspective in contrast to other standardization work in progress on software. This article presents a structured analysis of ISO 14143-1 to analyze its completeness and mapping to measurement principles and related concepts. This analysis is carried out following the structure of a process model for software engineering measurement methods, identifying the distinct steps involved, from the design of a measurement method to the exploitation of the measurement results. For each step of this process model, the proposed analysis identifies the strengths and weaknesses of the ISO 14143-1 standard. A summary of its key strengths and weaknesses is presented in the conclusion.

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)0.019
metaresearch head score (Gemma)0.033
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: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.019
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.008
Science and technology studies0.0020.005
Scholarly communication0.0070.010
Open science0.0020.003
Research integrity0.0020.003
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 head0.042
GPT teacher head0.269
Teacher spread0.227 · 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
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

Citations15
Published2003
Admission routes2
Has abstractyes

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