Data-driven parameterized algorithmics of graph modification problems(DAPA)

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The fundamental goals of DAPA have not changed substantially since the first project phase: the aim is to develop efficient parameterized algorithms for graph modification problems. Herein, we put special emphasis on data-driven parameterization, that is, the identification of promising parameters using real-world data. Often this includes problem-independent, so-called structural parameters, for example the number of connected components of the input graph. The development of efficient algorithms for the considered problems requires a deep understanding of the computational complexity with respect to these structural parameters. We aim to transfer positive algorithmic results to practical applications, including empirical evaluations. In the second project phase, we particularly plan to make increased use of methods and tools developed in the first phase.