Estimate reliability of component-based software sys-tem using modified neuro fuzzy model

  • Authors

    • Ravi Kumar Sharma Manav Rachna International University,Faridabad
    • Dr. Parul Gandhi Manav Rachna International University,Faridabad
    2017-05-24
    https://doi.org/10.14419/ijet.v6i2.7722
  • Component-Based Software Systems (CBSS), Fuzzy, Modified Neuro Fuzzy Inference System (MNFIS), Neuro Fuzzy, Reliability.

  • There are many algorithms and techniques for estimating the reliability of Component Based Software Systems (CBSSs). Accurate esti-mation depends on two factors: component reliability and glue code reliability. Still much more research is expected to estimate reliability in a better way. A number of soft computing approaches for estimating CBSS reliability has been proposed. These techniques learnt from the past and capture existing patterns in data. In this paper, we proposed new model for estimating CBSS reliability known as Modified Neuro Fuzzy Inference System (MNFIS). This model is based on four factors Reusability, Operational, Component dependency, Fault Density. We analyze the proposed model for diffent data sets and also compare its performance with that of plain Fuzzy Inference System. Our experimental results show that, the proposed model gives better reliability as compare to FIS.

  • References

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      [6] Kuldeep Singh Kaswan, Sunita Choudhary and Kapil Sharma, 2015. Software Reliability Modeling using Soft Computing Techniques: Critical Review, I.J. Information Technology and Computer Science, 2015, 07, 90-101. https://doi.org/10.5815/ijitcs.2015.07.10.

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  • How to Cite

    Sharma, R. K., & Gandhi, D. P. (2017). Estimate reliability of component-based software sys-tem using modified neuro fuzzy model. International Journal of Engineering & Technology, 6(2), 45-49. https://doi.org/10.14419/ijet.v6i2.7722