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This paper deals with the challenging problem of counting the number of solutions of a CSP, denoted #CSP. Recent progress have been made using search methods, such as BTD [15], which exploit the constraint graph structure in order to solve CSPs.We propose to adapt BTDfor solving the #CSP problem. The resulting exact counting method has a worst-case time complexity exponential in a specific graph parameter, called tree-width. For problems with sparse constraint graphs but large tree-width, we propose an iterative method which approximates the number of solutions by solving a partition of the set of constraints into a collection of partial chordal subgraphs. Its time complexity is exponential in the maximum clique size - the clique number - of the original problem, which can be much smaller than its tree-width. Experiments on CSP and SAT benchmarks shows the practical efficiency of our proposed approaches.