Performance impact of lazy deletion in metric trees for incremental clone analysis

Doing clone detection in multiple versions of a software can be expensive. Incremental clone detection is acknowledged to be a good method to make this process better. We extend existing ideas in incremental clone detection to metric trees using lazy deletion. We measured the execution time of the non-incremental and the incremental version of the clone detector and discovered that incremental clone detection can save a sizable amount of time even for versions separated by large variations. We discuss the results and propose some future research.