Mobile apps are becoming complex software systems that must be developed quickly and evolve continuously to fit new user requirements and execution contexts. However, addressing these requirements may result in poor design choices, also known as antipatterns, which may incidentally degrade software quality and performance. Thus, the automatic detection and tracking of antipatterns in this apps are important activities in order to ease both maintenance and evolution. Moreover, they guide developers to refactor their applications and thus, to improve their quality. While antipatterns are well-known in object-oriented applications, their study in mobile applications is still in its infancy. In this paper, we analyze the evolution of mobile apps quality on 3,568 versions of 106 popular Android applications downloaded from the Google Play Store. For this purpose, we use a tooled approach, called Paprika, to identify 3 object-oriented and 4 Android-specific antipatterns from binaries of mobile apps, and to analyze their quality along evolutions.