Masataka Nagura

SHINOBI: A Tool for Automatic Code Clone Detection in the IDE

Recent research has acknowledged that code clones decrease the maintainability and reliability of software programs, thus it is being regarded as one of the major factors to increase development/maintenance cost. We introduce SHINOBI, a novel code clone detection/modification tool that is designed to aid in recognizing and highlighting code clones during software maintenance tasks. SHINOBI is implemented as an add-in of Microsoft Visual Studio that automatically reports clones of modified snippets in real time.

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 Babas 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 Babas 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.

Code Clone Graph Metrics for Detecting Diffused Code Clones

Code clones (duplicated source code in a software system) are one of the major factors in decreasing maintainability. Many code clone detection methods have been proposed to find code clones automatically from large-scale software. However, it is still hard to find harmful code clones to improve maintainability because there are many code clones that should remain. Thus, to help find harmful code clones, we propose a code clone visualization method and a metrics application on the visualized information. Our method enables the location of harmful code clones diffused in a software system. We apply our method to three open source software programs and visualize their code clone information.