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Record W2901466745 · doi:10.5539/mas.v12n12p18

Service Composition in Service Oriented Architecture: A Survey

2018· article· en· W2901466745 on OpenAlexvenueno aff
Fatima Aladwan, Ahmad Alzghoul, Emad Mohammed Mahmoud Ali, Hussam N. Fakhouri, Israa Alzghoul

Bibliographic record

VenueModern Applied Science · 2018
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceService-oriented architectureScalabilityLoose couplingSoftware engineeringModular designReuseComponent (thermodynamics)Service (business)Software architectureComponent-based software engineeringArchitectureApplications architectureDistributed computingSoftwareOperating systemSoftware developmentComputer architectureWeb serviceProgramming languageEngineering

Abstract

fetched live from OpenAlex

AbstractService-Oriented Architecture (SOA) is a modular approach to software development based on the use of distributed, loose coupling replaceable components equipped with standardized interfaces for interaction over standardized protocols Component interfaces in a service-oriented architecture encapsulate the implementation details (operating system, platform, programming language) from the rest of the components, thereby enabling the combination and reuse of components to build complex distributed software packages, ensuring independence from the platforms and development tools used, facilitating scalability and manageability of the systems being created. In this paper we introduce a Service composition in service oriented architecture, it is present service composition with different approach used for composing services and provided.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.012
Science and technology studies0.0010.001
Scholarly communication0.0030.005
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.015
GPT teacher head0.244
Teacher spread0.229 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations6
Published2018
Admission routes1
Has abstractyes

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