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Record W2621693081 · doi:10.1109/ccece.2017.7946844

A reliability-aware framework for service-based software development

2017· article· en· W2621693081 on OpenAlexaff
Ian Andrusiak, Qusay H. Mahmoud

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsComputer scienceReliability (semiconductor)Service (business)Web serviceSoftware engineeringService providerSoftwareService-oriented architectureScheme (mathematics)Reliability engineeringWorld Wide WebOperating systemEngineering

Abstract

fetched live from OpenAlex

It is becoming more common to see software applications taking advantage of the many RESTful web services available publicly to meet their needs rather than developing an in-house solution. This introduces the problem where failures can occur in the network or on the service provider outside the influence of a developer. This paper introduces a reliability-aware framework with a focus on availability which applies concepts from a recovery block scheme to services provided publicly by different developers. The proposed framework allows developers to specify alternative services which meet the core specifications of their desired primary service. When a failure is determined to have occurred, the request to the primary service is mapped to an alternative service to complete the operation. A prototype implementation has been developed as a proof of concept of the design which has been evaluated on metrics based on potential use cases. The experimental results show that the system is successful at providing availability when failure occurs at a cost to overall performance.

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 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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.578
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0030.001
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 head0.023
GPT teacher head0.279
Teacher spread0.256 · 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 teacher head, 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

Citations2
Published2017
Admission routes1
Has abstractyes

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