Android devices include many embedded resources such as Camera, Media Player and Sensors. These resources require programmers to explicitly request and release them. Missing release operations might cause serious problems such as performance degradation or system crash. This kind of defects is called resource leak. Despite a large body of existing works on testing and analyzing Android apps, there still remain several challenging problems. In this work, we present Relda2, a light-weight and precise static resource leak detection tool. We first systematically collected a resource table, which includes the resources that the Android reference requires developers release manually. Based on this table, we designed a general approach to automatically detect resource leaks. To make a more precise inter-procedural analysis, we construct a Function Call Graph for each Android application, which handles function calls of user-defined methods and the callbacks invoked by the Android framework at the same time. To evaluate Relda2's effectiveness and practical applicability, we downloaded 103 apps from popular app stores and an open source community, and found 67 real resource leaks, which we have confirmed manually.

Android phones come with a host of hardware components embedded in them, such as Camera, Media Player and Sensor. Most of these components are exclusive resources or resources consuming more memory/energy than general. And they should be explicitly released by developers. Missing release operations of these resources might cause serious problems such as performance degradation or system crash. These kinds of defects are called resource leaks. This paper focuses on resource leak problems in Android apps, and presents our lightweight static analysis tool called Relda, which can automatically analyze an application's resource operations and locate the resource leaks. We propose an automatic method for detecting resource leaks based on a modified Function Call Graph, which handles the features of event-driven mobile programming by analyzing the callbacks defined in Android framework. Our experimental data shows that Relda is effective in detecting resource leaks in real Android apps.