Analysis of approach for predicting software defect density using static metrics

Now a day´s software development is growing rapidly. Due to this, there is also a rapid growth in the number of occurrences of defects. In this paper, defect density had been predicted using the Linear Regression Method and had been applied to Static Metrics. It helps to determine that to which module more reliability techniques should be applied. Static metric is used for prediction of defects which requires extraction of abstract information from the code. In this paper, the relationship has been established between the static metrics with defect density individually and jointly. This relationship is used to predict the number of defects. Simple and multiple linear regression statistical methods have been used for the analysis. The results reveal that which static metric is more useful in prediction of defect density and which metric is less useful and will also see that which metric has positive correlation or negative correlation with defects.