I've abstracted the concepts of Cluster, Clusters and ClusteringAlgorithm introducing those three abstract classes.
Then I introduced apache-commons-math3's DBSCAN algorithm in the package.
The original source code of the DBSCAN algorithm was slightly modified in order to fit to the news abstract classes.
Since now I can test both clustering algorithm (K-medoids and DBSCAN) with the same interface.

TODO:
Modify the DBSCAN source code in order to automatically return an additional cluster (with the NOISE labelled instances) with the real clusters.
Deleted a fake test.