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Compressed Suffix Array

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  • First Online:
Encyclopedia of Algorithms

Years and Authors of Summarized Original Work

  • 2000, 2003; Sadakane

  • 2000, 2005; Grossi, Vitter

  • 2000, 2005; Ferragina, Manzini

Problem Definition

Given a text string T = t1t2… t n over an alphabet \(\varSigma\) of size \(\sigma\), the suffix array A[1, n] is a permutation of the interval [1, n] that sorts the suffixes of T. More precisely, it satisfies T[A[i], n] < T[A[i + 1], n] for all 1 ≤ i < n, where “ < ” between strings is the lexicographical order. The suffix array is the canonical full-text index that allows to efficiently compute basic string matching queries on T.

The compressed suffix array (CSA) problem asks to replace A with a space-efficient data structure that is capable of efficiently computing A[i].

If a CSA does not require T to operate, and is capable of efficiently answering substring queries on T, it is called a self-index, as it can be seen as a replacement of T itself. Typical queries required from such an index are the following:

  • count(P): count how many times a...

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Recommended Reading

  1. Belazzougui D, Navarro G (2011) Alphabet-independent compressed text indexing. In: ESA, Saarbrücken, pp 748–759

    MATH  Google Scholar 

  2. Burrows M, Wheeler D (1994) A block sorting lossless data compression algorithm. Technical report 124, Digital Equipment Corporation

    Google Scholar 

  3. Ferragina P, Manzini G (2005) Indexing compressed texts. J ACM 52(4):552–581

    Article  MathSciNet  MATH  Google Scholar 

  4. Ferragina P, Giancarlo R, Manzini G, Sciortino M (2005) Boosting textual compression in optimal linear time. J ACM 52(4):688–713

    Article  MathSciNet  MATH  Google Scholar 

  5. Ferragina P, Manzini G, Mäkinen V, Navarro G (2007) Compressed representations of sequences and full-text indexes. ACM Trans Algorithms 3(2):20

    Article  MathSciNet  MATH  Google Scholar 

  6. Foschini L, Grossi R, Gupta A, Vitter JS (2006) When indexing equals compression: experiments with compressing suffix arrays and applications. ACM Trans Algorithms 2(4):611–639

    Article  MathSciNet  Google Scholar 

  7. Golynski A, Raman R, Srinivasa Rao S (2008) On the redundancy of succinct data structures. In: SWAT, Gothenburg, pp 148–159

    MATH  Google Scholar 

  8. Grossi R, Vitter J (2006) Compressed suffix arrays and suffix trees with applications to text indexing and string matching. SIAM J Comput 35(2):378–407

    Article  MathSciNet  MATH  Google Scholar 

  9. Grossi R, Gupta A, Vitter J (2003) High-order entropy-compressed text indexes. In: Proceedings of the 14th annual ACM-SIAM symposium on discrete algorithms (SODA), Baltimore, pp 841–850

    Google Scholar 

  10. Kärkkäinen J, Puglisi SJ (2011) Fixed block compression boosting in fm-indexes. In: SPIRE, Pisa, pp 174–184

    Google Scholar 

  11. Mäkinen V, Navarro G (2005) Succinct suffix arrays based on run-length encoding. Nord J Comput 12(1):40–66

    MathSciNet  MATH  Google Scholar 

  12. Mäkinen V, Navarro G (2008) Dynamic entropy-compressed sequences and full-text indexes. ACM Trans Algorithms 4(3):32

    Article  MathSciNet  MATH  Google Scholar 

  13. Manber U, Myers G (1993) Suffix arrays: a new method for on-line string searches. SIAM J Comput 22(5):935–948

    Article  MathSciNet  MATH  Google Scholar 

  14. Manzini G (2001) An analysis of the Burrows-Wheeler transform. J ACM 48(3):407–430

    Article  MathSciNet  MATH  Google Scholar 

  15. Navarro G, Mäkinen V (2007) Compressed full-text indexes. ACM Comput Surv 39(1): Article 2

    Google Scholar 

  16. Sadakane K (2003) New text indexing functionalities of the compressed suffix arrays. J Algorithms 48(2):294–313

    Article  MathSciNet  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Helsinki Institute for Information Technology (HIIT), University of Helsinki, Helsinki, Finland

    Djamal Belazzougui

  2. Department of Computer Science, Helsinki Institute for Information Technology (HIIT), University of Helsinki, Helsinki, Finland

    Veli Mäkinen

  3. Department of Computer Science, Helsinki Institute for Information Technology (HIIT), University of Helsinki, Helsinki, Finland

    Daniel Valenzuela

Authors
  1. Djamal Belazzougui
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  2. Veli Mäkinen
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  3. Daniel Valenzuela
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA

    Ming-Yang Kao

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Belazzougui, D., Mäkinen, V., Valenzuela, D. (2016). Compressed Suffix Array. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_82

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