Assessing the differences of clone detection methods used in the fault-prone module prediction

We have investigated through several experiments the differences in the fault-prone module prediction accuracy caused by the differences in the constituent code clone metrics of the prediction model. In the previous studies, they use one or more code clone metrics as independent variables to build an accurate prediction model. While they often use the clone detection method proposed by Kamiya et al. to calculate these metrics, the effect of the detection method on the prediction accuracy is not clear. In the experiment, we built prediction models using a dataset collected from an open source software project. The result suggests that the prediction accuracy is improved, when clone metrics derived from the various clone detection tool are used.