Satisfying a set of constraints is known as an instance of the constraint satisfaction problem (CSP), which is the subject of intense research in both artificial intelligence and operations research. Practical solution of CSP instances usually involves backtrack search. This is a complete approach that performs an exhaustive exploration of the search space of the instance to be solved. There have been considerable efforts during the last three decades to maximize the practical efficiency of backtrack search, relying on the concepts of constraint propagation, intelligent backtracking, restarting policy, variable (and value) ordering heuristic, and so on. In particular, the development of general‐purpose adaptive heuristics has shown impressive progress in guiding search.