ContextMobile devices, such as smartphones, have increased their capacity of information processing and sensors have been aggregated to their hardware. Such sensors allow capturing information from the environment in which they are introduced. As a result, mobile applications that use the environment and user information to provide services or perform context-based actions are increasingly common. This type of application is known as context-aware application. While software testing is an expensive activity in general, testing context-aware applications is an even more expensive and challenging activity. Thus, efforts are needed to automate testing for context-aware applications, particularly in the scope of Android, which is currently the most used operating system by smartphones.ObjectiveThis paper aims to identify and discuss the state-of-the-art tools that allow the automation of testing Android context-aware applications.MethodIn order to do so, we carried out a systematic mapping study (SMS) to find out the studies in the existing literature that describe or present Android testing tools. The discovered tools were then analyzed to identify their potential in testing Android context-aware applications.ResultA total of 68 works and 80 tools were obtained as a result of the SMS. From the identified tools, five are context-aware Android application testing tools, and five are general Android application testing tools, but support the test of the context-aware feature.ConclusionAlthough context-aware application testing tools do exist, they do not support automatic generation or execution of test cases focusing on high-level contexts. Moreover, they do not support asynchronous context variations.

中文翻译：

---

Android 上下文感知应用程序的测试工具：系统映射

ContextMobile 设备（例如智能手机）增加了其信息处理能力，并且传感器已聚合到其硬件中。这种传感器允许从引入它们的环境中捕获信息。因此，使用环境和用户信息来提供服务或执行基于上下文的操作的移动应用程序越来越普遍。这种类型的应用程序称为上下文感知应用程序。虽然软件测试通常是一项昂贵的活动，但测试上下文感知应用程序是一项更加昂贵和具有挑战性的活动。因此，需要努力对上下文感知应用程序进行自动化测试，特别是在 Android 的范围内，这是目前智能手机最常用的操作系统。目的本文旨在确定和讨论允许自动化测试 Android 上下文感知应用程序的最先进工具。方法为此，我们进行了系统映射研究 (SMS)，以找出在描述或展示 Android 测试工具的现有文献。然后对发现的工具进行分析，以确定它们在测试 Android 上下文感知应用程序中的潜力。结果 作为 SMS 的结果，总共获得了 68 个作品和 80 个工具。从确定的工具来看，5个是上下文感知Android应用测试工具，5个是通用Android应用测试工具，但都支持对上下文感知特性的测试。 结论虽然上下文感知应用测试工具确实存在，它们不支持自动生成或执行专注于高级上下文的测试用例。此外，它们不支持异步上下文变化。