Object-oriented software fault prediction using neural networks

This paper introduces two neural network based software fault prediction models using Object-Oriented metrics. They are empirically validated using a data set collected from the software modules developed by the graduate students of our academic institution. The results are compared with two statistical models using five quality attributes and found that neural networks do better. Among the two neural networks, Probabilistic Neural Networks outperform in predicting the fault proneness of the Object-Oriented modules developed.