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Introducing Fuzzy Logic for Software Reliability Admeasurement

    Authors

    • Vishnupriya S 1
    • Nirsandh Ganesan 2
    • Ms. Piriyanga 3
    • Kiruthiga Devi 3

    1 Research Engineer, KEDS GROUP R&D, Coimbatore, Tamilnadu, India

    2 Research & Design Engineer, KEDS GROUP R&D, Coimbatore, Tamilnadu, India

    3 Research Intern, KEDS GROUP R&D, Coimbatore, Tamilnadu, India

,

Document Type : Research Article

10.47392/irjash.2022.056
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Abstract

 
Software reliability estimation using fuzzy logic is shown in this article. The suggested approach tries to assign target dependability to each of its parts. The initial stage in estimating reliability is to combine the aspects of the experts in this proposed method. The system’s element of proportionality is evaluated in the second phase. Employing the equations of defuzzification, the system ele- ments undergo the process of defuzzification. We must compute the weightage of subset of the framework (i.e. module) when we have obtained precise data. The subset’s reliability is estimated, at the root of its weightage. By testing the most often used functions first and less frequently used functions second, the portrait of operational status is determined, which is one of the most impor- tant criteria for ensuring successful testing and increased reliability (Ebeling). Efficiency has improved in comparison to the prior results obtained. It aids in the assignment of reliability to every subsets prior to the frame working of real system. This even takes Operation status into account as element of propor- tionality, which assists in providing reliability to the subsets frequently used, designing a framework for reliability admeasurements, advantageous for all the subsets present.

Keywords

  • Software reliability
  • Fuzzy logic
  • defuzzification
  • admeasurements

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    • Article View: 188
    • PDF Download: 93
International Research Journal on Advanced Science Hub
Volume 4, Issue 09
September 2022
Page 222-226
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History
  • Receive Date: 02 August 2022
  • Revise Date: 06 September 2022
  • Accept Date: 16 September 2022
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  • Article View: 188
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APA

S, V. , Ganesan, N. , Piriyanga, M. and Devi, K. (2022). Introducing Fuzzy Logic for Software Reliability Admeasurement. International Research Journal on Advanced Science Hub, 4(09), 222-226. doi: 10.47392/irjash.2022.056

MLA

S, V. , , Ganesan, N. , , Piriyanga, M. , and Devi, K. . "Introducing Fuzzy Logic for Software Reliability Admeasurement", International Research Journal on Advanced Science Hub, 4, 09, 2022, 222-226. doi: 10.47392/irjash.2022.056

HARVARD

S, V., Ganesan, N., Piriyanga, M., Devi, K. (2022). 'Introducing Fuzzy Logic for Software Reliability Admeasurement', International Research Journal on Advanced Science Hub, 4(09), pp. 222-226. doi: 10.47392/irjash.2022.056

CHICAGO

V. S , N. Ganesan , M. Piriyanga and K. Devi, "Introducing Fuzzy Logic for Software Reliability Admeasurement," International Research Journal on Advanced Science Hub, 4 09 (2022): 222-226, doi: 10.47392/irjash.2022.056

VANCOUVER

S, V., Ganesan, N., Piriyanga, M., Devi, K. Introducing Fuzzy Logic for Software Reliability Admeasurement. International Research Journal on Advanced Science Hub, 2022; 4(09): 222-226. doi: 10.47392/irjash.2022.056

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