Optimization of Object-Oriented Metrics Using Hopfield Neural Network

Download Now
Provided by: International Journal of Soft Computing and Engineering (IJSCE)
Topic: Enterprise Software
Format: PDF
In this paper, the authors examined the application of artificial neural network for software quality prediction using object-oriented metrics. Quality estimation includes estimating maintainability of software. In this paper, maintenance effort was chosen as the dependent variable and principal components of object-oriented metrics as the dependent variables. They are prediction the number of lines per changed per class. Two neural network models are used; they are ward neural network and Hopfield neural network. The artificial neural network possesses the advantages of predicting software quality accurately and identifies the defects by efficient discovery mechanisms.
Download Now

Find By Topic