Explainable constraint solving is a sub-field of explainable AI (XAI) concerned with explaining constraint (optimization) problems. Although constraint models are explicit: they are written down in terms of individual constraints that need to be satisfied, the solution to such models can be non-trivial to understand. This hands-on tutorial demonstrates the type of questions a user can have about (non)-solutions, as well as reviewing what kind of computational tools are available today to answer such questions. It covers classical methods and more recent advances in the field such as step-wise explanations, constraint relaxation methods and counterfactual solutions. Link