In this talk, we will present a general pattern based on contractor programming for designing a global optimization solver. This approach allows to solve problems with a wide variety of constraints. The complexity and the performance of the algorithm rely on the construction of contractors which characterize the feasible region. We illustrate the methodology on a $H_\infty$ control synthesis under structural constraints.