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Detecting Antipatterns in Android Apps

机译:在Android应用中检测反模式

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摘要

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 constraints may result in poor design choices, known as antipatterns, which may incidentally degrade software quality and performance. Thus, the automatic detection of antipatterns is an important activity that eases both maintenance and evolution tasks. Moreover, it guides 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 their infancy. In this paper, we propose a tooled approach, called Paprika, to analyze Android applications and to detect object-oriented and Android-specific antipatterns from binaries of mobile apps. We validate the effectiveness of our approach on a set of popular mobile apps downloaded from the Google Play Store.
机译:移动应用程序正在变成复杂的软件系统,必须快速开发并不断发展以适应新的用户需求和执行上下文。但是,解决这些约束可能会导致设计选择不佳(称为反模式),从而可能会偶然降低软件质量和性能。因此,反模式的自动检测是一项重要的活动,可以简化维护和开发任务。此外,它指导开发人员重构其应用程序,从而提高其质量。虽然反模式在面向对象的应用程序中是众所周知的,但它们在移动应用程序中的研究仍处于起步阶段。在本文中,我们提出了一种名为Paprika的工具化方法,用于分析Android应用程序并从移动应用程序的二进制文件中检测面向对象和Android特定的反模式。我们通过从Google Play商店下载的一系列流行的移动应用验证了我们的方法的有效性。

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