We investigate the effect of two suggested problem properties,
basin size contrast and global to local optima contrast, on the performance
of different basin identification methods, namely nearest-better
clustering, detect-multimodal, and Jarvis-Patrick clustering, individually,
or in combinations. Problem instances are generated and validated
according to predefined property values and obtained  result data is
modeled in order to  detect similarities that may be interpreted as
effects of the stated properties. We also give recommendations
concerning usage of basin identification methods in different situations.