Skip to main content
SpringerLink
Log in

A metrics framework for measuring quality of a web service as it evolves

  • Original Article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

In service-oriented architecture, a web service evolves over time. Changes in a service may affect the quality of service for the service provider as well as for the service consumer. The quality of a service is measured from its structural perspective and therefore the proposed metrics are defined considering the web service description language document of a service. In this paper, a suite of metrics consisting of service evolution metric, service client-code evolution metric and service usefulness evolution metric has been proposed which measures service evolution for the service provider, impact of service evolution on the client code and on the usefulness for the service consumer. The time complexity of the proposed metrics is linear. The study of correlation between these metrics is conducted which indicates to the service provider whether the changes made in the service have tangible benefits for the consumer. To show the applicability of the metrics, real world data as well as simulated data has been used. Zuse framework has been used to theoretically validate the metrics. All the metrics are above the ordinal scale.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Balfagih Z, Hassan MF (2009) Quality model for web services from multi-stakeholders’ perspective In: International conference on information management and engineering, ICIME’09. pp 287–291

  • Calero C, Piattini M, Pascual C, Serrano MA (2001) Towards data warehouse quality metrics. In: DMDW

  • Choi SW, Kim SD (2008) A quality model for evaluating reusability of services in soa. In 10th IEEE conference on e-commerce technology and the fifth IEEE conference on enterprise computing, e-commerce and e-services. pp 293–298

  • Choi SW, Her JS, Kim SD (2007) Modeling QoS Attributes and metrics for evaluating services in soa considering consumers’ perspective as the first class requirement. In: Asia-Pacific service computing conference The 2nd IEEE. pp 398–405

  • Curtis B (1980) Measurement and experimentation in software engineering. Proc IEEE 68(9):1144–1157

    Article  Google Scholar 

  • Drouin N, Badri M, Touré F (2013) Metrics and software quality evolution: a case study on open source software. Int J Comput Theory Eng 5(3):523

    Article  Google Scholar 

  • Eclipse (2016) E-business technologies: foundations and practice http://www.eclipse.org/webtools/community/education/web/t320/Generating_a_client_from_WSDL.pdf

  • Erl T (2005) Service-oriented architecture: concepts, technology, and design. Pearson Education India

  • Erl T (2008) SOA: principles of service design, vol 1. Prentice Hall, Upper Saddle River

    Google Scholar 

  • Fang R, Lam L, Fong L, Frank D, Vignola C, Chen Y, Du N (2007) A version-aware approach for web service directory. In: IEEE international conference on web services ICWS. pp 406–413

  • Fenton N, Bieman J (2014) Software metrics: a rigorous and practical approach. CRC Press, Boca Raton

    Book  MATH  Google Scholar 

  • Fokaefs M, Stroulia E (2014) Wsdarwin: studying the evolution of web service systems. In: Bouguettaya A, Sheng QZ, Daniel F (eds) Advanced web services. Springer, New York, pp 199–223

  • Fokaefs M, Mikhaiel R, Tsantalis N, Stroulia E, Lau A (2011) An empirical study on web service evolution. In: IEEE international conference on web services (ICWS). pp 49–56

  • Juric MB, Sasa A, Brumen B, Rozman I (2009) WSDL and UDDI extensions for version support in web services. J Syst Softw 82(8):1326–1343

    Article  Google Scholar 

  • Kalepu S, Krishnaswamy S, Loke SW (2003) Verity: a QoS metric for selecting web services and providers. In: IEEE fourth international conference on web information systems engineering workshops proceedings. pp 131–139

  • Lee Y (2010) QoS metrics for service level measurement for SOA environment. In: 6th International conference on advanced information management and service (IMS). pp 509–514

  • Lee Y, Yang J, Chang KH (2007) Metrics and evolution in open source software. In: 7th International conference on quality software (QSIC). pp 191–197

  • Lehman MM (1996) Laws of software evolution revisited. In: Schäfer W (ed) European workshop on software process technology. Springer, Berlin, pp 108–124

  • Lehman MM, Ramil JF, Wernick PD, Perry DE, Turski WM (1997) Metrics and laws of software evolution-the nineties view. In: Proceedings of fourth international software metrics symposium. IEEE, pp 20–32

  • Mens T, Demeyer S (2001) Future trends in software evolution metrics. In: Proceedings of the 4th international workshop on principles of software evolution. ACM, pp 83–86

  • Nadanam P, Rajmohan R (2012). QoS evaluation for web services in cloud computing. In: Third international conference on computing communication and networking technologies (ICCCNT). IEEE, pp 1–8

  • Oh SH, La HJ, Kim SD (2011) A reusability evaluation suite for cloud services. In: E-business engineering (ICEBE). pp 111–118

  • Oracle (2010) The Java EE 5 Tutorial. http://docs.oracle.com/javaee/5/tutorial/doc/bnayn.html

  • Papazoglou MP (2008) The challenges of service evolution. In: International conference on advanced information systems engineering. Springer, Berlin, pp 1–15

  • Papazoglou MP, Andrikopoulos V, Benbernou S (2011) Managing evolving services. IEEE Softw 28(3):49–55

    Article  Google Scholar 

  • Parnas DL (1994) Software aging. In: Proceedings of the 16th international conference on software engineering. IEEE Computer Society Press, pp 279–287

  • Pivotal (2016) Consuming a SOAP web service. https://spring.io/guides/gs/consuming-web-service/

  • Rud D, Schmietendorf A, Dumke R (2007) Resource metrics for service-oriented infrastructures. Proc SEMSOA 2007:90–98

    Google Scholar 

  • Van Gurp J, Bosch J (2002) Design erosion: problems and causes. J Syst Softw 61(2):105–119

    Article  Google Scholar 

  • World Wide Web Consortium (2001). http://www.w3.org/TR/wsdl

  • Senivongse T, Phacharintanakul N, Ngamnitiporn C, Tangtrongchit M (2010) A capability granularity analysis on web service invocations. In: Proceedings of the world congress on Engineering and computer science, vol 1. pp 20–22

  • Zaikin M (2012) Create a web service client for a SOAP based web service. http://java.boot.by/ocewsd6-guide/ch06.html

  • Zhang H, Kim S (2010) Monitoring software quality evolution for defects. IEEE Softw 27(4):58

    Article  Google Scholar 

  • Zuse H (1998) A framework of software measurement. Walter de Gruyter, Berlin, New York

Download references

Author information

Authors and Affiliations

  1. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India

    Rachna Kohar & N. Parimala

Authors
  1. Rachna Kohar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. N. Parimala
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rachna Kohar.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kohar, R., Parimala, N. A metrics framework for measuring quality of a web service as it evolves. Int J Syst Assur Eng Manag 8 (Suppl 2), 1222–1236 (2017). https://doi.org/10.1007/s13198-017-0591-y

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-017-0591-y

Keywords

Search

Navigation