Mobile applications are becoming complex software systems that must be developed quickly and evolve regularly to fit new user requirements and execution contexts. However, addressing these constraints may result in poor design choices, known as antipatterns, which may degrade software quality and performance. Thus, the automatic detection of antipatterns is an important activity that eases the future maintenance and evolution tasks. Moreover, it helps developers to refactor theirapplications and thus, to improve their quality. While antipatternsare well-known in object-oriented applications, their study in mobile applications is still in their infancy. In this paper, we presents a tooled approach, called PAPRIKA , to analyze Android applications and to detect object-oriented and Android-specific antipatterns from binaries of applications.