An Approach for LPF Table Computation

  • Supaporn ChairungseeEmail author
  • Thana Charuphanthuset
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1062)


In this article, we introduce a new solution for the Longest Previous Factor (LPF) table computation. The LPF table is the table that stores the maximal length of factors re-occurring at each position of a string and this table is useful for text compression. The LPF table has the important role for computational biology, data compression and string algorithms. In this paper, we present an approach to compute the LPF table of a string from its suffix heap. The algorithm runs in linear time with linear memory space.


Longest previous factor table Data compression Suffix heap Text compression 


  1. 1.
    Bell, T.C., Clearly, J.G., Witten, I.H.: Text Compression. Prentice Hall Inc., Upper Saddle River (1990)Google Scholar
  2. 2.
    Crochemore, M., Hancart, C., Lecroq, T.: Algorithms on Strings. Cambridge University Press, Cambridge (2007)CrossRefGoogle Scholar
  3. 3.
    Crochemore, C., Ilie, L.: Computing longest previous factor in linear time and applications. Inf. Process. Lett. 106(2), 75–80 (2008)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Crochemore, M., Ilie, L., Iliopoulos, C.S., Kubica, M., Rytter, W., Waleń, T.: LPF computation revisited. In: Fiala, J., Kratochvíl, J., Miller, M. (eds.) IWOCA 2009. LNCS, vol. 5874, pp. 158–169. Springer, Heidelberg (2009). Scholar
  5. 5.
    Crochemore, M., Iliopoulos, C.S., Kubica, M., Rytter, W., Waleń, T.: Efficient algorithms for two extensions of LPF table: the power of suffix arrays. In: van Leeuwen, J., Muscholl, A., Peleg, D., Pokorný, J., Rumpe, B. (eds.) SOFSEM 2010. LNCS, vol. 5901, pp. 296–307. Springer, Heidelberg (2010). Scholar
  6. 6.
    Crochemore, M., Ilie, L., Iliopoulos, C.S., Kubica, M., Rytter, W., Wale, T.: Computing the longest previous factor. Eur. J. Comb. 34(1), 15–26 (2013)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Crochemore, C., Tischler, G.: Computing longest previous nonoverlapping factors. Inf. Process. Lett. 111, 291–295 (2011)CrossRefGoogle Scholar
  8. 8.
    Drozdek, A.: Data Structures and Algorithms in C++. Cengage Learning, Boston (2013)Google Scholar
  9. 9.
    Gagie, T., Hon, W.-K., Ku, T.-H.: New algorithms for position heaps. In: Fischer, J., Sanders, P. (eds.) CPM 2013. LNCS, vol. 7922, pp. 95–106. Springer, Heidelberg (2013). Scholar
  10. 10.
    Kongsen, J., Chairungsee, S.: Using suffix tray and longest previous factor for pattern searching. In: International Conference on Information Technology, Singapore, Singapore (2017)Google Scholar
  11. 11.
    Pu, I.M.: Fundamental Data Compression. A Butterworth-Heinemann, Oxford (2006)Google Scholar
  12. 12.
    Storer, J.A.: Data Compression: Methods and Theory. Computer Science Press, New York (1988)Google Scholar
  13. 13.
    Ziv, J., Lempel, A.: A universal algorithm for sequential data compression. IEEE Trans. Inf. Theory. 23, 337–343 (1977)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Walailak UniversityNakhonsithammaratThailand
  2. 2.Suratthani Rajabhat UniversitySuratthaniThailand

Personalised recommendations