Prediction of Software Quality by Object Oriented Metric in Neural Networks

Authors

  • G. Rajendra  Research Scholar, Department Computer Science, Rayalaseema University, Kurnool, Andhra Pradesh, India
  • Dr. M. Babu Reddy  HOD, Department of Computer Science, Krishna University, Machilipatnam, Andhra Pradesh, India

Keywords:

Software Quality Metrics, Classification, Software Testing, Fault-Prone, Fuzzy Logic and Software Inceptions.

Abstract

This paper provides a new strategy of early software top quality forecast and position. Quality forecast is done by identifying application segments as fault-prone (FP) or not fault-prone (NFP). Furthermore, modules are rated using application analytics and unclear purchasing criteria on the basis of their degree of mistake proneness. Ranking of fault-prone component along with category discovered to be a new strategy to help in showing priority for and assigning test sources to the specific application segments. The design precision is verified through sample programs available on different software applications. The results noticed are discovered appealing, in comparison to some of the previous models.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-01-30

Issue

Volume 4, Issue 1, January-February-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
G. Rajendra, Dr. M. Babu Reddy, " Prediction of Software Quality by Object Oriented Metric in Neural Networks, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 1, pp.1619-1625, January-February-2018.