Service Design Metrics to Predict IT-Based Drivers of Service Oriented Architecture Adoption

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The key factors for deploying successful services is centered on the service design practices adopted by an enterprise. The design level information should be validated and measures are required to quantify the structural attributes. The metrics at this stage will support an early discovery of design flaws and help designers to predict the capabilities of service oriented architecture (SOA) adoption. In this work, we take a deeper look at how we can forecast the key SOA capabilities infrastructure efficiency and service reuse from the service designs modeled by SOA modeling language. The proposed approach defines metrics based on the structural and domain level similarity of service operations. The proposed metrics are analytically validated with respect to software engineering metrics properties. Moreover, a tool has been developed to automate the proposed approach and the results indicate that the metrics predict the SOA capabilities at the service design stage. This work can be further extended to predict the business based capabilities of SOA adoption such as flexibility and agility.

Original languageEnglish
Title of host publication2018 9th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538644300
DOIs
Publication statusPublished - Oct 16 2018
Event9th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2018 - Bengaluru, India
Duration: Jul 10 2018Jul 12 2018

Other

Other9th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2018
CountryIndia
CityBengaluru
Period7/10/187/12/18

Keywords

  • ervice design
  • infrastructure efficiency
  • metrics
  • service interface diagram
  • service reuse
  • SoaML

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Safety, Risk, Reliability and Quality

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  • Cite this

    Pulparambil, S., Baghdadi, Y., Al Hamadani, A., & Al-Badawi, M. (2018). Service Design Metrics to Predict IT-Based Drivers of Service Oriented Architecture Adoption. In 2018 9th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2018 [8494072] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCCNT.2018.8494072