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Record W3118932225 · doi:10.5539/nct.v5n2p15

A Comparative Study of Formal Approaches for Web Service Oriented Architecture

2020· article· en· W3118932225 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNetwork and Communication Technologies · 2020
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceWeb serviceOrchestrationSoftware engineeringService-oriented architectureExecutableWeb modelingWS-PolicyBusiness Process Execution LanguageWS-I Basic ProfileWorld Wide WebWeb standardsWeb developmentWeb application securityProgramming languageWeb intelligence

Abstract

fetched live from OpenAlex

The security in web service oriented architecture (WSOA) development has become a critical need and goal. WSOA as service-oriented architecture (SOA) designs the software as services and uses the services as platforms. Web services orchestration describes how web services can interact with each other from an operational perspective. Many languages allow expression of executable processes to implementing web services orchestration. These languages are used to describe how the interactions between multiple services are coordinated to achieve a goal. However, the operational semantics of each of the structures of these languages is not formally defined and they have limitations regarding the reasoning and the verification of the web services compositions. Several studies and approaches have been proposed in this context, are devoted to the formalization of web services orchestrations and allow some verification of their behavior; these approaches are partial solutions to the problem of development of the safe composition. We explore the advantages and limitations of more than fourteen approaches and research work. We propose a model for comparison between works, studies, and approaches in this field. The proposed model adopts the concepts of the formalization and the automation of development processes.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.571

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.048
GPT teacher head0.256
Teacher spread0.207 · 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