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One of the most important structural parameters of graphs is treewidth, a measure for the " tree-likeness " and thus in many cases an indicator for the hardness of problem instances. The smaller the treewidth, the closer the graph is to a tree and the more efficiently the underlying instance often can be solved. However , computing the treewidth of a graph(More)
We present algorithms for the propositional model counting problem #SAT. The algorithms utilize tree decompositions of certain graphs associated with the given CNF formula; in particular we consider primal, dual, and incidence graphs. We describe the algorithms coherently for a direct comparison and with sufficient detail for making an actual implementation(More)
Hypertree decompositions of hypergraphs are a generalization of tree decompositions of graphs. The corresponding hypertree-width is a measure for the cyclicity and therefore tractability of the encoded computation problem. Many NP-hard decision and computation problems are known to be tractable on instances whose structure corresponds to hypergraphs of(More)
The literature provides several structural decomposition methods for identifying tractable subclasses of the constraint satisfaction problem. Generalized hypertree decomposition is the most general of such decomposition methods. Although the relationship to other structural decomposition methods has been thoroughly investigated, only little research has(More)
We review the concepts of hypertree decomposition and hypertree width from a graph theoretical perspective and report on a number of recent results related to these concepts. We also show – as a new result – that computing hypertree decompositions is fixed-parameter intractable. This paper reports about the recently introduced concept of hypertree(More)