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Software Quality Prediction Using Fuzzy Logic Technique

Author

Listed:
  • Saumendra Pattnaik

    (Siksha'O'Anusandhan University, Odisha, India)

  • Binod Kumar Pattanayak

    (Siksha'O'Anusandhan University, Odisha, India)

  • Srikanta Patnaik

    (Siksha'O'Anusandhan University, Odisha, India)

Abstract

In the global market, the value of software quality is a major factor in software industries. In a majority of cases, software quality needs to be quantified and measured. Previously, many models like the ISO model, the McCall model, the Boehm model, etc., have been used for the quantification of the parameters which determine the software quality. The software quality can be judged by analyzing all the characteristics of the product. In this article, a new pragmatic model which is the modification of the existing ISO Model has been proposed in order for the quantification of the software quality factors in a more precise way. Because of the nature of the attributes which determine the software quality, a Fuzzy logic-based approach is considered to be a better technique among various existing machine learning techniques. Here, the simulink tool is used for constructing the running model which helps the net quality of the software.

Suggested Citation

  • Saumendra Pattnaik & Binod Kumar Pattanayak & Srikanta Patnaik, 2019. "Software Quality Prediction Using Fuzzy Logic Technique," International Journal of Information Systems in the Service Sector (IJISSS), IGI Global, vol. 11(2), pages 51-71, April.
    • Handle: RePEc:igg:jisss0:v:11:y:2019:i:2:p:51-71
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