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Evaluate and Measure Agile Software Efficiency by the Integrated Strategy of Fuzzy MOORA and AHP

In: Predictive Analytics in System Reliability

Author

Listed:
  • Abhishek Srivastava

    (Amity University)

  • P. K. Kapur

    (Amity University)

  • Alakkshendra Rawat

    (Amity University)

  • Aditya Mittal

    (Amity University)

  • Vidhyashree Nagaraju

    (The University of Tulsa)

Abstract

Now a day’s every business stakeholder wants that they will get best output from their software development teams. There are many software developing methodologies present in the market right now and every methodology has its own advantages and disadvantages, even Agile has certain disadvantages, but agile always try to give the best output product to their client and always welcomes the spontaneous market changes, which most of the software developing methodologies are unable to deliver. Now the question arises that how to measure the efficiency of this software development or testing methodology. In this paper, we plan to use an approach or propose an integrated strategy of Fuzzified Multi Objective Optimization on the bases of Ratio Analysis (MOORA) and Analytic Hierarchy Process (AHP) to determine the efficiency of Agile software. In this we first extracted some important factors used in agile software development through correlational research and with the help of agile certified professionals, then we compared those factors with help of the above-mentioned tools Fuzzy based MOORA and AHP. The methodology utilized in this certain research study article acts as very vital toolkit for the researchers or professionals who want to measure and evaluate the efficiency of such software development technology.

Suggested Citation

  • Abhishek Srivastava & P. K. Kapur & Alakkshendra Rawat & Aditya Mittal & Vidhyashree Nagaraju, 2023. "Evaluate and Measure Agile Software Efficiency by the Integrated Strategy of Fuzzy MOORA and AHP," Springer Series in Reliability Engineering, in: Vijay Kumar & Hoang Pham (ed.), Predictive Analytics in System Reliability, pages 159-173, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-05347-4_11
    DOI: 10.1007/978-3-031-05347-4_11
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