Abstract
(I) We revisit the algorithmic problem of finding all triangles in a graph \(G=(V,E)\) with n vertices and m edges. According to a result of Chiba and Nishizeki (1985), this task can be achieved by a combinatorial algorithm running in \(O(m \alpha ) = O(m^{3/2})\) time, where \(\alpha = \alpha (G)\) is the graph arboricity. We provide a new very simple combinatorial algorithm for finding all triangles in a graph and show that is amenable to the same running time analysis. We derive these worst-case bounds from first principles and with very simple proofs that do not rely on classic results due to Nash-Williams from the 1960s.
(II) We extend our arguments to the problem of finding all small complete subgraphs of a given fixed size. We show that the dependency on m and \(\alpha \) in the running time \(O(\alpha ^{\ell -2} \cdot m)\) of the algorithm of Chiba and Nishizeki for listing all copies of \(K_\ell \), where \(\ell \ge 3\), is asymptotically tight.
(III) We give improved arboricity-sensitive running times for counting and/or detection of copies of \(K_\ell \), for small \(\ell \ge 4\). A key ingredient in our algorithms is, once again, the algorithm of Chiba and Nishizeki. Our new algorithms are faster than all previous algorithms in certain high-range arboricity intervals for every \(\ell \ge 7\).
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Dumitrescu, A., Lingas, A. (2023). Finding Small Complete Subgraphs Efficiently. In: Hsieh, SY., Hung, LJ., Lee, CW. (eds) Combinatorial Algorithms. IWOCA 2023. Lecture Notes in Computer Science, vol 13889. Springer, Cham. https://doi.org/10.1007/978-3-031-34347-6_16
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