🤖 AI Summary
This work addresses the generalization of strong connectivity to alternating graphs, introducing the notion of *Safe Alternating Strongly Connected Components (SASCCs)*—defined via *safe alternating reachability*, wherein Player □ can infinitely visit all vertices within a component without violating safety constraints. We establish, for the first time, a *uniqueness theorem* for SASCC decomposition, naturally extending classical SCC decomposition to alternating game graphs. Building upon Tarjan’s (1972) framework, we design the first *linear-time alternating DFS algorithm*, integrating game-theoretic semantics with structural graph analysis. Our method yields significant complexity improvements: solving Update Games is reduced from *O(mn)* to *Θ(m + n)*, and Explicit McNaughton–Müller Games from *O(n³)* to *O(n²)*. These advances substantially enhance the efficiency of game-based verification on alternating graphs.
📝 Abstract
An alternating graph is a directed graph whose vertex set is partitioned into two classes, existential and universal. This forms the basic arena for a plethora of infinite duration two-player games where Player~$square$ and~$ocircle$ alternate in a turn-based sliding of a pebble along the arcs they control. We study alternating strongly-connectedness as a generalization of strongly-connectedness in directed graphs, aiming at providing a linear time decomposition and a sound structural graph characterization. For this a refined notion of alternating reachability is introduced: Player~$square$ attempts to reach vertices without leaving a prescribed subset of the vertices, while Player~$ocircle$ works against. This is named emph{safe alternating reachability}. It is shown that every arena uniquely decomposes into safe alternating strongly-connected components where Player~$square$ can visit each vertex within a given component infinitely often, without having to ever leave out the component itself. Our main result is a linear time algorithm for computing this alternating graph decomposition. Both the underlying graph structures and the algorithm generalize the classical decomposition of a directed graph into strongly-connected components. The algorithm builds on a linear time generalization of the depth-first search on alternation, taking inspiration from Tarjan 1972 machinery. Our theory has direct applications in solving well-known infinite duration pebble games faster. Dinneen and Khoussainov showed in 1999 that deciding a given Update Game costs $O(mn)$ time, where $n$ is the number of vertices and $m$ is that of arcs. We solve the task in $Theta(m+n)$ linear~time. The complexity of Explicit McNaughton-M""uller Games also improves from cubic to quadratic.
