  The growing utilization of planning tools in practical scenarios has sparked
an interest in generating multiple high-quality plans. Consequently, a range of
computational problems under the general umbrella of top-quality planning were
introduced over a short time period, each with its own definition. In this
work, we show that the existing definitions can be unified into one, based on a
dominance relation. The different computational problems, therefore, simply
correspond to different dominance relations. Given the unified definition, we
can now certify the top-quality of the solutions, leveraging existing
certification of unsolvability and optimality. We show that task
transformations found in the existing literature can be employed for the
efficient certification of various top-quality planning problems and propose a
novel transformation to efficiently certify loopless top-quality planning.
