DIALIGN has been shown to perform well on those data sets in BAliBASE that contain large insertions and deletions. On the other hand, it is often outperformed by global alignment methods on those data sets where homology extends over the entire sequence length but similarity is low at the primary-sequence level. For the further development and improvement of the program, it is crucial to find out which components of DIALIGN are to blame for the inferiority of the program on this type if sequence families. One possibility is that biologically meaningful alignments on BAliBASE would have high numerical scores, but the greedy heuristic used by DIALIGN is inefficient and returns low-scoring alignments that do not align the core blocs correctly. In this case, one would use more efficient optimisation strategies to improve the performance of DIALIGN on BAliBASE. On the other hand, it is possible that the scoring function used in DIALIGN assigns highest scores to biologically wrong alignments. In this case, an improved optimisation algorithm would not lead to any improvement in the biological quality of the output alignments and it would be necessary to improve the objective function used by the program.