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Dynamic Matching Algorithms in Practice

Authors Monika Henzinger , Shahbaz Khan , Richard Paul , Christian Schulz

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Author Details

Monika Henzinger
  • University of Vienna, Faculty of Computer Science, Austria
Shahbaz Khan
  • Department of Computer Science, University of Helsinki, Finland
Richard Paul
  • University of Vienna, Faculty of Computer Science, Austria
Christian Schulz
  • University of Vienna, Faculty of Computer Science, Austria

Funding

The research leading to these results has received funding from the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007-2013) /ERC grant agreement No. 340506.

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Monika Henzinger, Shahbaz Khan, Richard Paul, and Christian Schulz. Dynamic Matching Algorithms in Practice. In 28th Annual European Symposium on Algorithms (ESA 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 173, pp. 58:1-58:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020) https://doi.org/10.4230/LIPIcs.ESA.2020.58

Abstract

In recent years, significant advances have been made in the design and analysis of fully dynamic maximal matching algorithms. However, these theoretical results have received very little attention from the practical perspective. Few of the algorithms are implemented and tested on real datasets, and their practical potential is far from understood. In this paper, we attempt to bridge the gap between theory and practice that is currently observed for the fully dynamic maximal matching problem. We engineer several algorithms and empirically study those algorithms on an extensive set of dynamic instances.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Graph algorithms
Keywords
  • Matching
  • Dynamic Matching
  • Blossom Algorithm

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Supplementary Materials

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