Finding level-ancestors in dynamic trees

  • Paul F. Dietz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 519)


Single Vertex Linear Time Algorithm Vertex Number Heavy Path Major Vertex 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    M. Ajtai, M. Fredman, and J. Komlós. Hash functions for priority queues. Information and Control, 63(3):217–225, December 1984.Google Scholar
  2. [2]
    Omer Berkman and Uzi Vishkin. Recursive *-tree parallel data-structure. In Proc. 30th Ann. IEEE Symp. on Foundations of Computer Science, pages 196–202, October 1989.Google Scholar
  3. [3]
    Omer Berkman and Uzi Vishkin. Finding level-ancestors in trees. Technical Report UMIACSTR-91-9, Institute for Advanced Computer Studies, U. of Maryland, January 1991.Google Scholar
  4. [4]
    Michael L. Fredman and Dan E. Willard. Blasting through the information theoretic barrier with fusion trees. In Proc. 22nd ACM STOC, pages 1–7, May 1990.Google Scholar
  5. [5]
    Harold N. Gabow. Data structures for weighted matching and nearest common ancestor. Technical Report CU-CS-478-90, U. of Colorado at Boulder, Department of Computer Science, June 1990. An earlier version was presented at the 1990 Symp. on Discrete Algorithm.Google Scholar
  6. [6]
    D. Harel and R. E. Tarjan. Fast algorithms for finding nearest common ancestors. SIAM J. On Computing, 13(2):338–355, 1984.Google Scholar
  7. [7]
    Robert E. Tarjan. Applications of path compression on balanced trees. Journal of the ACM, 26(4):690–715, Oct. 1979.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Paul F. Dietz
    • 1
  1. 1.Department of Computer ScienceUniversity of RochesterRochester

Personalised recommendations