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Record W2009999392 · doi:10.1109/coginf.2006.365704

Design of an Integrated Hyper Specification Documentation Tool

2006· article· en· W2009999392 on OpenAlexaff
Jian Huang, Yingxu Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCognitive Computing and Networks
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceDocumentationHyperlinkSoftware engineeringReadabilityMaintainabilityProgramming languageUnified Modeling LanguageTechnical documentationSoftwareWorld Wide WebWeb page

Abstract

fetched live from OpenAlex

This paper presents an integrated hyper specification documentation (IHSD) methodology and tool for coherent software engineering documentation. The IHSD tool is designed for automatically creating hyperlinks between system conceptual models in UML; formal models in real-time process algebra (RTPA); and code in a programming language. The three types of design documents for a system in UML, RTPA, and C++ program are stored in a standard HTML file format. When a built-in hyperlink in a system model is clicked, the corresponding HTML page in the integrated file is show up. The IHSD method provides a powerful and convenient integration of traditionally separated system design documents by hyperlinks in a coherent environment. Under the support of the IHSD tool, readers can traverse from any point of interested objects to any other ones among the conceptual and formal models of systems as well as corresponding programs. Therefore, the readability and maintainability of large-scale software systems are dramatically improved

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)0.008
metaresearch head score (Gemma)0.013
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: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.013
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0040.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.004

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 head0.024
GPT teacher head0.251
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 designSimulation or modeling
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

Citations1
Published2006
Admission routes1
Has abstractyes

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