• Journal of KIISE:Computer Systems and Theory
• /
• v.34 no.5_6
• /
• pp.169-175
• /
• 2007

Suffix arrays, fundamental full-text index data structures, can be efficiently used where patterns are queried many times. Although many useful full-text index data structures have been proposed, their O(nlogn)-bit space consumption motivates researchers to develop more space-efficient ones. However, their space efficient versions such as the compressed suffix array and the FM-index have been developed; those can not reduce the practical working space because their constructions are based on the existing suffix array. Recently, two direct construction algorithms of compressed suffix arrays from the text without constructing the suffix array have been proposed. In this paper, we compare practical performance of these algorithms of compressed suffix arrays with that of various algorithms of suffix arrays by measuring the construction times, the peak memory usages during construction and the sizes of their final outputs.

• Journal of KIISE:Computer Systems and Theory
• /
• v.34 no.8
• /
• pp.319-326
• /
• 2007

To perform fast searching in massive data such as DNA strings, the most efficient method is to construct full-text index data structures of given strings. The widely used full-text index structures are suffix trees and suffix arrays. Since the suffix may uses less space than the suffix tree, the suffix array is proper for DNA strings. Previously developed construction algorithms of suffix arrays are not suitable for DNA strings since those are designed for integer alphabets. We propose a fast algorithm to construct suffix arrays on DNA strings whose alphabet sizes are fixed by 4. We reduce the construction time by improving encoding and merging steps on Kim et al.[1]'s algorithm. Experimental results show that our algorithm constructs suffix arrays on DNA strings 1.3-1.6 times faster than Kim et al.'s algorithm, and also for other algorithms in most cases.