Object oriented software quality prediction using general regression neural networks
Selvadurai Kanmani, V. Rhymend Uthariaraj, Venkataraman Sankaranarayanan, P. Thambidurai · ACM SIGSOFT Software Engineering Notes · 2004
This paper discusses the application of General Regression Neural Network (GRNN) for predicting the software quality attribute -- fault ratio. This study is carried out using static Object-Oriented (OO) measures (64 in total) as the independent variables and fault ratio as the dependent variable. Software metrics used include those concerning inheritance, size, cohesion and coupling. Prediction models are designed using 15 possible combinations of the four categories of the measures. We also tested the goodness of fit of the neural network model with the standard parameters. Our study is conducted in an academic institution with the software developed by students of Undergraduate/Graduate courses.