Prediction of Software Quality by Object Oriented Metric in Neural Networks
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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