The field of numerical methods for partial differential equations is witnessing significant developments, with a focus on improving the efficiency and robustness of existing methods. Researchers are exploring new preconditioning techniques, stabilization methods, and domain decomposition algorithms to enhance the performance of iterative solvers. Notably, the development of parameter-robust preconditioners and the application of generalized residual cutting methods are showing promise in addressing long-standing challenges. Furthermore, investigations into the theoretical properties of advanced discretization methods, such as the ADER-DG method, are providing valuable insights into their approximation properties, convergence, and stability. Some noteworthy papers include: the introduction of a parameter-robust preconditioner for a hybridizable discontinuous Galerkin discretization of Biot's consolidation model, which demonstrates improved performance in numerical examples. The stabilization of BiCGSTAB by the generalized residual cutting method is also a significant contribution, as it enhances the robustness of this widely used iterative algorithm.