Copy number alterations (CNAs) represent an important component of genetic variation and play a significant role in many human diseases. Development of array comparative genomic hybridization (aCGH) technology has made it possible to identify CNAs. Identification of recurrent CNAs represents the first fundamental step to provide a list of genomic regions which form the basis for further biological investigations. The main problem in recurrent CNAs discovery is related to the need to distinguish between functional changes and random events without pathological relevance. Within-sample homogeneity represents a common feature of copy number profile in cancer, so it can be used as additional source of information to increase the accuracy of the results. Although several algorithms aimed at the identification of recurrent CNAs have been proposed, no attempt of a comprehensive comparison of different approaches has yet been published.