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Record W2119525869 · doi:10.5381/jot.2006.5.4.a5

UML Profiles for Real-Time Systems and their Applications.

2006· article· en· W2119525869 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Journal of Object Technology · 2006
Typearticle
Languageen
FieldComputer Science
TopicSoftware System Performance and Reliability
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUnified Modeling LanguageComputer scienceReal-time computingSoftware engineeringEmbedded systemProgramming languageSoftware

Abstract

fetched live from OpenAlex

Real-time systems (RTS) have strict timing constraints and limited resources. The satisfaction of RTS timing constraints is required for their correction. In order to reduce the cost due to late discovery of design flaws and/or violations of timing constraints of RTS as well as to speed up their development to cope with time-to-market requirements, it is important to validate, at early stages of the development process, the functional and nonfunctional properties of RTS. In addition, RTS complexity is continuously increasing which makes their design very challenging. UML, a graphical object-oriented modeling language, is suitable to deal with this complexity. UML also supports predictive, quantitative analysis through its real-time profiles. The objective of this paper is to review the most important UML profiles for real-time from the academia, the industry and/or standard organizations; and the research activity that revolves around these profiles.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.614
Threshold uncertainty score0.179

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.005
GPT teacher head0.221
Teacher spread0.216 · 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