An empirical evaluation of fault-proneness models

Planning and allocating resources for testing is difficult and it is usually done on empirical basis, often leading to unsatisfactory results. The possibility of early estimating the potential faultiness of software could be of great help for planning and executing testing activities. Most research concentrates on the study of different techniques for computing multivariate models and evaluating their statistical validity, but we still lack experimental data about the validity of such models across different software applications.This paper reports an empirical study of the validity of multivariate models for predicting software fault-proneness across different applications. It shows that suitably selected multivariate models can predict fault-proneness of modules of different software packages.