TY - GEN
T1 - Service Design Metrics to Predict IT-Based Drivers of Service Oriented Architecture Adoption
AU - Pulparambil, Supriya
AU - Baghdadi, Youcef
AU - Al-Hamdani, Abdullah
AU - Al-Badawi, Mohammed
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/16
Y1 - 2018/10/16
N2 - 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.
AB - 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.
KW - SoaML
KW - ervice design
KW - infrastructure efficiency
KW - metrics
KW - service interface diagram
KW - service reuse
UR - http://www.scopus.com/inward/record.url?scp=85056865895&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85056865895&partnerID=8YFLogxK
U2 - 10.1109/ICCCNT.2018.8494072
DO - 10.1109/ICCCNT.2018.8494072
M3 - Conference contribution
AN - SCOPUS:85056865895
T3 - 2018 9th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2018
BT - 2018 9th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2018
Y2 - 10 July 2018 through 12 July 2018
ER -