Incremental SCC Maintenance in Sparse Graphs

Authors Aaron Bernstein, Aditi Dudeja, Seth Pettie



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Author Details

Aaron Bernstein
  • Rutgers University, New Brunswick, NJ, USA
Aditi Dudeja
  • Rutgers University, New Brunswick, NJ, USA
Seth Pettie
  • University of Michigan, Ann Arbor, MI, USA

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Aaron Bernstein, Aditi Dudeja, and Seth Pettie. Incremental SCC Maintenance in Sparse Graphs. In 29th Annual European Symposium on Algorithms (ESA 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 204, pp. 14:1-14:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/LIPIcs.ESA.2021.14

Abstract

In the incremental cycle detection problem, edges are added to a directed graph (initially empty), and the algorithm has to report the presence of the first cycle, once it is formed. A closely related problem is the incremental topological sort problem, where edges are added to an acyclic graph, and the algorithm is required to maintain a valid topological ordering. Since these problems arise naturally in many applications such as scheduling tasks, pointer analysis, and circuit evaluation, they have been studied extensively in the last three decades. Motivated by the fact that in many of these applications, the presence of a cycle is not fatal, we study a generalization of these problems, incremental maintenance of strongly connected components (incremental SCC). Several incremental algorithms in the literature which do cycle detection and topological sort in directed acyclic graphs, such as those by [Michael A. Bender et al., 2016] and [Haeupler et al., 2012], also generalize to maintain strongly connected components and their topological sort in general directed graphs. The algorithms of [Haeupler et al., 2012] and [Michael A. Bender et al., 2016] have a total update time of O(m^{3/2}) and O(m⋅ min{m^{1/2},n^{2/3}}) respectively, and this is the state of the art for incremental SCC. But the most recent algorithms for incremental cycle detection and topological sort ([Bernstein and Chechik, 2018] and [Bhattacharya and Kulkarni, 2020]), which yield total (randomized) update time Õ(min{m^{4/3}, n²}), do not extend to incremental SCC. Thus, there is a gap between the best known algorithms for these two closely related problems. In this paper, we bridge this gap by extending the framework of [Bhattacharya and Kulkarni, 2020] to general directed graphs. More concretely, we give a Las Vegas algorithm for incremental SCCs with an expected total update time of Õ(m^{4/3}). A key ingredient in the algorithm of [Bhattacharya and Kulkarni, 2020] is a structural theorem (first introduced in [Bernstein and Chechik, 2018]) that bounds the number of "equivalent" vertices. Unfortunately, this theorem only applies to DAGs. We show a natural way to extend this structural theorem to general directed graphs, and along the way we develop a significantly simpler and more intuitive proof of this theorem.

Subject Classification

ACM Subject Classification
  • Theory of computation → Dynamic graph algorithms
Keywords
  • Directed Graphs
  • Strongly Connected Components
  • Dynamic Graph Algorithms

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