  We consider the question of distribution testing (specifically, uniformity
and closeness testing) in the streaming setting, \ie under stringent memory
constraints. We improve on the results of Diakonikolas, Gouleakis, Kane, and
Rao (2019) by providing considerably simpler algorithms, which remove some
restrictions on the range of parameters and match their lower bounds.
