Since clone detection results cannot fully reflect the features of clones, clone genealogies extraction from multiple versions can be used to uncover the patterns and characteristics exhibited by clones in the evolving system. A clone genealogy extraction method named FCG was proposed. FCG first mapped clones between each adjacent versions and then identified clone evolution patterns. All of the results were combined to get clone genealogies. Experiments on 6 open source systems found that the average lifetime of clones in current version is over 70 percent of the total number of studied versions, and most of them do not change, which indicates that majority of clones can be well maintained. While some unstable clones may be defect potential, and needs to be modified or refactoring. Results show that FCG can efficiently extract clone genealogies, which contributes to a better understanding of clones and provides insights on targeted management of clones.

The activities of the programmers including copy, paste and modify result in a lot of code clone in the software systems. However, the inconsistent change of code clone is the main reason that causes program error and increases maintenance costs in the evolutionary process of the software version. To solve this problem, a new research method was proposed. The mapping relationship between the clone groups was built at first. Then the theme of lineal cloning cluster was extracted using Latent Dirichlet Allocation (LDA) model. Finally, the inconsistent change probability of code clone was predicted. A software which contains eight versions was tested and an obvious discrimination was got. The experimental results show that the method can effectively predict the probability of inconsistent change and be used for evaluating quality and credibility of software.