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

TitleService Design Metrics to Predict IT-Based Drivers of Service Oriented Architecture Adoption
Publication TypeConference Paper
Year of Publication2018
AuthorsPulparambil, S., Baghdadi, Y., Al-Hamdani, A., Al-Badawi, M.
Conference Name2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT)
Date PublishedJuly 2018
PublisherIEEE
ISBN Number978-1-5386-4430-0
KeywordsBusiness, business based capabilities, Complexity theory, Couplings, design flaws, ervice design, infrastructure efficiency, IT-based driver, Measurement, Metrics, Protocols, pubcrawl, resilience, Resiliency, Scalability, service design metrics, service interface diagram, service oriented architecture, service reuse, service-oriented architecture, SOA modeling language, SoaML, software engineering metrics properties, software metrics, structural domain level similarity, Unified modeling language, work factor metrics
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.

URLhttps://ieeexplore.ieee.org/document/8494072
DOI10.1109/ICCCNT.2018.8494072
Citation Keypulparambil_service_2018