Do Memories Haunt You? An Automated Black Box Testing Approach for Detecting Memory Leaks in Android Apps

Memory leaks represent a remarkable problem for mobile app developers since a waste of memory due to bad programming practices may reduce the available memory of the device, slow down the apps, reduce their responsiveness and, in the worst cases, they may cause the crash of the app. A common cause o...

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Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.12217-12231
Main Authors: Amalfitano, Domenico, Riccio, Vincenzo, Tramontana, Porfirio, Fasolino, Anna Rita
Format: Article
Language:English
Subjects:
Aging
Android
Android activity lifecycle
Android testing
Applications programs
Leaks
Life cycle analysis
memory leak
Memory management
Mobile computing
Random access memory
resource leak
Smart phones
Software
Testing
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Summary:Memory leaks represent a remarkable problem for mobile app developers since a waste of memory due to bad programming practices may reduce the available memory of the device, slow down the apps, reduce their responsiveness and, in the worst cases, they may cause the crash of the app. A common cause of memory leaks in the specific context of Android apps is the bad handling of the events tied to the Activity Lifecycle. In order to detect and characterize these memory leaks, we present FunesDroid, a tool-supported black box technique for the automatic detection of memory leaks tied to the Activity Lifecycle in Android apps. FunesDroid implements a testing approach that can find memory leaks by analyzing unnecessary heap object replications after the execution of three different sequences of Activity Lifecycle events. In the paper, we present an exploratory study that shows the capability of the proposed technique to detect memory leaks and to characterize them in terms of their size, persistence and growth trend. The study also illustrates how memory leak causes can be detected with the support of the information provided by the FunesDroid tool.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2966522