Structural decomposition methods, such as generalized hypertree decompositions, have been successfully used for solving constraint
satisfaction problems (CSPs). As decompositions can be reused to solve CSPs with the same constraint scopes, investing resources in
computing good decompositions is beneficial, even though the computation itself is hard. Unfortunately, current methods need to
compute a completely new decomposition even if the scopes change only slightly. In this paper, we make the first steps toward solving
the problem of updating the decomposition of a CSP so that it becomes a valid decomposition of a new CSP
′ produced by some
modification of . Even though the problem is hard in theory, we propose and implement a framework for effectively updating GHDs.
The experimental evaluation of our algorithm strongly suggests practical applicability
