Theoretical analysis demonstrates efficient polynomial-time algorithms in graphs parameterized by vertex integrity, revealing substantial speedups over tree-depth methods.
We study the computational complexity of several polynomial-time-solvable graph problems parameterized by vertex integrity, a measure of a graph's vulnerability to vertex removal in terms of connectivity. Vertex integrity is the smallest number ι such that there is a set S of ι' ≤ ι vertices such that every connected component of $G-S$ contains at most ι-ι' vertices. It is known that the vertex integrity lies between the well-studied parameters vertex cover number and tree-depth. Alon and Yuster [ESA 2007] designed algorithms for graphs with small vertex cover number using fast matrix multiplications. We demonstrate that fast matrix multiplication can also be effectively used when parameterizing by vertex integrity ι by developing efficient algorithms for problems including an O(ιω-1n)-time algorithm for computing the girth of a graph, randomized O(ιω - 1n)-time algorithms for Maximum Matching and for finding any induced four-vertex subgraph except for a clique or an independent set, and an O(ι(ω-1)/2n²) ⊆ O(ι0.687 n²)-time algorithm for All-Pairs Shortest Paths. These algorithms can be faster than previous algorithms parameterized by tree-depth, for which fast matrix multiplication is not known to be effective.
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Bentert et al. (2024) studied this question.
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