Quality of Service Centric Web Service Composition: Assessing Composition Impact Scale towards Fault Proneness

Quality of Service Centric Web Service Composition: Assessing Composition Impact Scale towards Fault Proneness

Sujatha Varadi

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G Appa Rao

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GITAM University

Quality of Service Centric Web Service Composition: Assessing Composition Impact Scale towards Fault Proneness

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Abstract

Service composition in service oriented architecture is an important activity. In regard to achieve the quality of service and secured activities from the web service compositions, they need to be verified about their impact towards fault proneness before deploying that service composition. Henceforth, here in this paper, we devised a novel statistical approach to assess the service composition impact scale towards fault proneness. The devised model explores the higher and lower ranges of the service composition impact scale, which is from the knowledge of earlier compositions that are notified as fault prone.

References

11 Cites in Article

Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Sujatha Varadi. 2015. \u201cQuality of Service Centric Web Service Composition: Assessing Composition Impact Scale towards Fault Proneness\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 14 (GJCST Volume 14 Issue C9): .

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GJCST Volume 14 Issue C9
Pg. 13- 17

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

composition support service composition impact scale service descriptor impact scale web service composition fault pronen web service compositions

Submission ReceivedDecember 14, 2013
Peer Review Double Blind
Handling Editor
Accepted January 4, 2014
Published January 15, 2014

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v1.2

Issue date

January 21, 2015

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Article Matrices

Total Score: 102

Country: India

Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering

Authors: Sujatha Varadi, G Appa Rao (PhD/Dr. count: 0)

View Count (all-time): 253

Total Views (Real + Logic): 8450

Total Downloads (simulated): 2168

Publish Date: 2015 01, Wed

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Total Views: 8450

Total Downloads: 2168

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