An Empirical Study of Fault Prediction with Code Clone Metrics

In this paper, we present a replicated study to predict fault-prone modules with code clone metrics to follow Baba's experiment. We empirically evaluated the performance of fault prediction models with clone metrics using 3 datasets from the Eclipse project and compared it to fault prediction w...

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Bibliographic Details
Main Authors: Kamei, Y., Sato, H., Monden, A., Kawaguchi, S., Uwano, H., Nagura, M., Matsumoto, K., Ubayashi, N.
Format: Conference Proceeding
Language:English
Subjects:
Cloning
Code clone
Correlation
Empirical study
Fault prediction
Logistic regression analysis
Logistics
Measurement
Predictive models
Product metrics
Software
Software reliability
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Summary:In this paper, we present a replicated study to predict fault-prone modules with code clone metrics to follow Baba's experiment. We empirically evaluated the performance of fault prediction models with clone metrics using 3 datasets from the Eclipse project and compared it to fault prediction without clone metrics. Contrary to the original Baba's experiment, we could not significantly support the effect of clone metrics, i.e., the result showed that F1-measure of fault prediction was not improved by adding clone metrics to the prediction model. To explain this result, this paper analyzed the relationship between clone metrics and fault density. The result suggested that clone metrics were effective in fault prediction for large modules but not for small modules.
DOI:10.1109/IWSM-MENSURA.2011.12