Dušan Knop ; Martin Koutecký ; Tomáš Masařík ; Tomáš Toufar - Simplified Algorithmic Metatheorems Beyond MSO: Treewidth and Neighborhood Diversity

lmcs:5017 - Logical Methods in Computer Science, December 4, 2019, Volume 15, Issue 4 - https://doi.org/10.23638/LMCS-15(4:12)2019
Simplified Algorithmic Metatheorems Beyond MSO: Treewidth and Neighborhood DiversityArticle

Authors: Dušan Knop ORCID; Martin Koutecký ORCID; Tomáš Masařík ORCID; Tomáš Toufar ORCID

    This paper settles the computational complexity of model checking of several extensions of the monadic second order (MSO) logic on two classes of graphs: graphs of bounded treewidth and graphs of bounded neighborhood diversity. A classical theorem of Courcelle states that any graph property definable in MSO is decidable in linear time on graphs of bounded treewidth. Algorithmic metatheorems like Courcelle's serve to generalize known positive results on various graph classes. We explore and extend three previously studied MSO extensions: global and local cardinality constraints (CardMSO and MSO-LCC) and optimizing the fair objective function (fairMSO). First, we show how these extensions of MSO relate to each other in their expressive power. Furthermore, we highlight a certain "linearity" of some of the newly introduced extensions which turns out to play an important role. Second, we provide parameterized algorithm for the aforementioned structural parameters. On the side of neighborhood diversity, we show that combining the linear variants of local and global cardinality constraints is possible while keeping the linear (FPT) runtime but removing linearity of either makes this impossible. Moreover, we provide a polynomial time (XP) algorithm for the most powerful of studied extensions, i.e. the combination of global and local constraints. Furthermore, we show a polynomial time (XP) algorithm on graphs of bounded treewidth for the same extension. In addition, we propose a general procedure of deriving XP algorithms on graphs on bounded treewidth via formulation as Constraint Satisfaction Problems (CSP). This shows an alternate approach as compared to standard dynamic programming formulations.

    Volume: Volume 15, Issue 4
    Published on: December 4, 2019
    Accepted on: November 25, 2019
    Submitted on: December 7, 2018
    Keywords: Computer Science - Computational Complexity,Computer Science - Logic in Computer Science,F.2.2, G.2.2,F.2.2,G.2.2

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