Suffix arrays: a new method for on-line string searches
SIAM Journal on Computing
Large-scale C++ software design
Large-scale C++ software design
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Proceedings of the 16th Conference on Foundations of Software Technology and Theoretical Computer Science
Opportunistic data structures with applications
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Replacing suffix trees with enhanced suffix arrays
Journal of Discrete Algorithms - SPIRE 2002
New text indexing functionalities of the compressed suffix arrays
Journal of Algorithms
Compressed Suffix Arrays and Suffix Trees with Applications to Text Indexing and String Matching
SIAM Journal on Computing
ACM Computing Surveys (CSUR)
Space-efficient static trees and graphs
SFCS '89 Proceedings of the 30th Annual Symposium on Foundations of Computer Science
Broadword implementation of rank/select queries
WEA'08 Proceedings of the 7th international conference on Experimental algorithms
Algorithm engineering: bridging the gap between algorithm theory and practice
Algorithm engineering: bridging the gap between algorithm theory and practice
| Hi-index | 0.02 |
The suffix array of a string s of length n over the alphabet Σ is the permutation that gives us the lexicographic order of all suffixes of s . This popular index can be used to solve many problems in sequence analysis. In practice, one limitation of this data structure is its size of n logn bits, while the size of the text is n log|Σ | bits. For this reason compressed suffix arrays (CSAs) were introduced. The size of these CSAs is asymptotically less than or equal to the text size if the text is compressible, while maintaining O (log *** n ) access time to the elements (0 *** ≤ 1). The goal of a good CSA implementation is to provide fast access time to the elements while using minimal space for the CSA. Both access time and space depend on the choice of a self-delimiting code for compression. We show that the Fibonacci code is superior to the Elias *** code for strings that are low compressible. Our second contribution are two new broadword methods that support the decoding of Fibonacci encoded numbers on 64 bit architectures. Furthermore, our experiments show that the use of known broadword methods speed up the decoding of Elias *** code for strings that are high compressible, like XML. Finally, we provide a new efficient C++ library for succinct data structures which includes a generic CSA for further experiments.