Lowest common ancestors in trees and directed acyclic graphs

  • Authors:

  • Michael A. Bender;Martín Farach-Colton;Giridhar Pemmasani;Steven Skiena;Pavel Sumazin

  • Affiliations:

  • Department of Computer Science, State University of New York at Stony Brook, Stony Brook, NY;Department of Computer Science, Rutgers University, Piscataway, NJ;Department of Computer Science, State University of New York at Stony Brook, Stony Brook, NY;Department of Computer Science, State University of New York at Stony Brook, Stony Brook, NY;Department of Computer Science, Portland State University, Portland, Oregon

  • Venue:
  • Journal of Algorithms
  • Year:
  • 2005

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Abstract

We study the problem of finding lowest common ancestors (LCA) in trees and directed acyclic graphs (DAGs). Specifically, we extend the LCA problem to DAGs and study the LCA variants that arise in this general setting. We begin with a clear exposition of Berkman and Vishkin's simple optimal algorithm for LCA in trees. Their ideas lay the foundation for our work on LCA problems in DAGs. We present an algorithm that finds all-pairs-representative LCA in DAGs in Õ(n2.688) operations, provide a transitive-closure lower bound for the all-pairs-representative-LCA problem, and develop an LCA-existence algorithm that preprocesses the DAG in transitive-closure time. We also present a suboptimal but practical O(n3) algorithm for all-pairs-representative LCA in DAGs that uses ideas from the optimal algorithms in trees and DAGs. Our results reveal a close relationship between the LCA, all-pairs-shortest-path, and transitive-closure problems.We conclude the paper with a short experimental study of LCA algorithms in trees and DAGs. Our experiments and source code demonstrate the elegance of the preprocessing-query algorithms for LCA in trees. We show that for most trees the suboptimal Θ(n log n)-preprocessing Θ(1)-query algorithm should be preferred, and demonstrate that our proposed O (n3) algorithm for all-pairs-representative LCA in DAGs performs well in both low and high density DAGs.