
Graph parameters such as the clique number and the chromatic number are central in many areas, ranging from computer networks to linguistics to computational neuroscience to social networks. In particular, the chromatic number of a graph can be applied in solving practical tasks as diverse as pattern matching, scheduling jobs to machines, allocating registers in compiler optimization, and even solving Sudoku puzzles. Typically, however, the underlying graphs are subject to (often minor) changes. To make these applications of graph parameters robust, it is important to know which graphs are stable in the sense that adding or deleting single edges or vertices does not change them. We initiate the study of stability of graphs in terms of their computational complexity. We show for various central graph parameters that deciding the stability of a given graph is complete for Θ2p, a well-known complexity class in the second level of the polynomial hierarchy.
Journal of Computer and System Sciences, 123
ISSN:0022-0000
ISSN:1090-2724
FOS: Computer and information sciences, coDP, Parallel Access to NP, Analysis of algorithms and problem complexity, Clique, difference polynomial time, Colorability, Computational Complexity (cs.CC), DP, Vertex cover, Difference polynomial time, Stability; Robustness; Complexity; Local Modifications; Colorability; Vertex Cover; Clique; Independent Set; Satisfiability; Unfrozenness; Criticality; DP; coDP; Parallel Access to NP, Satisfiability, Robustness, Criticality, Local Modifications, Independent Set, Complexity, stability, vertex cover, 004, parallel access to NP, Computer Science - Computational Complexity, satisfiability, Graph theory (including graph drawing) in computer science, Vertex Cover, Parallel access to NP, Stability; Colorability; Vertex cover; Satisfiability; Difference polynomial time; Parallel access to NP, Unfrozenness, Stability, colorability
FOS: Computer and information sciences, coDP, Parallel Access to NP, Analysis of algorithms and problem complexity, Clique, difference polynomial time, Colorability, Computational Complexity (cs.CC), DP, Vertex cover, Difference polynomial time, Stability; Robustness; Complexity; Local Modifications; Colorability; Vertex Cover; Clique; Independent Set; Satisfiability; Unfrozenness; Criticality; DP; coDP; Parallel Access to NP, Satisfiability, Robustness, Criticality, Local Modifications, Independent Set, Complexity, stability, vertex cover, 004, parallel access to NP, Computer Science - Computational Complexity, satisfiability, Graph theory (including graph drawing) in computer science, Vertex Cover, Parallel access to NP, Stability; Colorability; Vertex cover; Satisfiability; Difference polynomial time; Parallel access to NP, Unfrozenness, Stability, colorability
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