  We describe decomposition during search (DDS), an integration of And/Or tree
search into propagation-based constraint solvers. The presented search
algorithm dynamically decomposes sub-problems of a constraint satisfaction
problem into independent partial problems, avoiding redundant work.
  The paper discusses how DDS interacts with key features that make
propagation-based solvers successful: constraint propagation, especially for
global constraints, and dynamic search heuristics.
  We have implemented DDS for the Gecode constraint programming library. Two
applications, solution counting in graph coloring and protein structure
prediction, exemplify the benefits of DDS in practice.
