Dynamic Trees in Practice

  • Robert E. Tarjan
  • Renato F. Werneck
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4525)

Abstract

Dynamic tree data structures maintain forests that change over time through edge insertions and deletions. Besides maintaining connectivity information in logarithmic time, they can support aggregation of information over paths, trees, or both. We perform an experimental comparison of several versions of dynamic trees: ST-trees, ET-trees, RC-trees, and two variants of top trees (self-adjusting and worst-case). We quantify their strengths and weaknesses through tests with various workloads, most stemming from practical applications. We observe that a simple, linear-time implementation is remarkably fast for graphs of small diameter, and that worst-case and randomized data structures are best when queries are very frequent. The best overall performance, however, is achieved by self-adjusting ST-trees.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Robert E. Tarjan
    • 1
    • 2
  • Renato F. Werneck
    • 3
  1. 1.Department of Computer Science, Princeton University, Princeton, NJ 08544USA
  2. 2.Hewlett-Packard Laboratories, 1501 Page Mill Rd., Palo Alto, CA 94304USA
  3. 3.Microsoft Research Silicon Valley, 1065 La Avenida, Mountain View, CA 94043USA

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