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BDD-Based Algorithm for SCC Decomposition of Edge-Coloured Graphs

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BENEŠ Nikola BRIM Luboš PASTVA Samuel ŠAFRÁNEK David

Rok publikování 2022
Druh Článek v odborném periodiku
Časopis / Zdroj Logical Methods in Computer Science
Fakulta / Pracoviště MU

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Citace
www https://lmcs.episciences.org/9198
Doi http://dx.doi.org/10.46298/LMCS-18(1:38)2022
Klíčová slova strongly connected components; symbolic algorithm; BDD
Popis Edge-coloured directed graphs provide an essential structure for modelling and analysis of complex systems arising in many scientific disciplines (e.g. feature-oriented systems, gene regulatory networks, etc.). One of the fundamental problems for edge-coloured graphs is the detection of strongly connected components, or SCCs. The size of edge-coloured graphs appearing in practice can be enormous both in the number of vertices and colours. The large number of vertices prevents us from analysing such graphs using explicit SCC detection algorithms, such as Tarjan's, which motivates the use of a symbolic approach. However, the large number of colours also renders existing symbolic SCC detection algorithms impractical. This paper proposes a novel algorithm that symbolically computes all the monochromatic strongly connected components of an edge-coloured graph. In the worst case, the algorithm performs O(p . n . log n) symbolic steps, where p is the number of colours and n is the number of vertices. We evaluate the algorithm using an experimental implementation based on binary decision diagrams (BDDs). Specifically, we use our implementation to explore the SCCs of a large collection of coloured graphs (up to 2(48)) obtained from Boolean networks - a modelling framework commonly appearing in systems biology.

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