An efficient performance testing of web services

Muhammad Hasnain, Muhammad Fermi Pasha, Imran Ghani, Muhammad Imran Babar

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

3 Citations (Scopus)

Abstract

To simulate the concurrent users' workload, this paper proposes a performance testing approach and novel average performance measuring (APM) metric for assessing the web services performance. It extracts the response time, throughput, and response code metrics information to build an efficient performance-related issues identification approach that detects performance faults earlier with less effort or expense. Multiple open-source and commercial performance testing tools are used in the information technology (IT) industry to analyze the performance of web services. Practitioners rely only on either response time or throughput metric to evaluate the performance of web services, which is not sufficient for a comprehensible performance testing of web services. Our proposed performance testing approach is more convenient and straightforward to perform performance testing of web services. Moreover, experiment results show that the proposed APM metric is efficient in the evaluation of performance testing approaches.

Original languageEnglish
Title of host publicationProceedings - 22nd International Multitopic Conference, INMIC'19
EditorsMuhammad Asim
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages170-178
Number of pages8
ISBN (Electronic)9781728140001, 9781728140018
ISBN (Print)9781728140025
DOIs
Publication statusPublished - 2019
EventIEEE International Multioptic Conference 2019 - Islamabad, Pakistan
Duration: 29 Nov 201930 Nov 2019
Conference number: 22nd
https://ieeexplore.ieee.org/xpl/conhome/9006915/proceeding (Proceedings)

Conference

ConferenceIEEE International Multioptic Conference 2019
Abbreviated titleINMIC 2019
Country/TerritoryPakistan
CityIslamabad
Period29/11/1930/11/19
Internet address

Keywords

  • Apm metric
  • Faults identification
  • Load testing
  • Performance testing
  • Web services

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