Systematic testing for resource leaks in Android applications

Yan, Dacong; Yang, Shengqian; Rountev, Atanas

doi:10.1109/issre.2013.6698894

Cited by 45 publications

(34 citation statements)

References 31 publications

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“…Aspect‐oriented programming can spot memory leaks at runtime, as discussed by Jain and Gopalani, but that work has not been extended from Java to Android yet. Testing has been used to find leaks by Yan et al They identify a sequence of dangerous user actions, which often lead to a leak, and replay them automatically to simulate dangerous behaviors. Testing has been applied to some common memory leak patterns by Shahriar et al, similar to those in Section 2.…”

Section: Related Workmentioning

confidence: 99%

Practical static analysis of context leaks in Android applications

2018

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Summary Android native applications, written in Java and distributed in APK format, are widely used in mobile devices. Their specific pattern of use lets the operating system control the creation and destruction of resources, such as activities and services (contexts). Programmers are not supposed to interfere with such life cycle events. Otherwise, contexts might be leaked, ie, they will never be deallocated from memory, or be deallocated late, leading to memory exhaustion and frozen applications. In practice, it is easy to write incorrect code, which hinders garbage collection of contexts and leads to context leakages. In this work, we present a novel static analysis method that finds context leaks in Android code. We apply this analysis to APKs translated into Java bytecode. We provide a formal analysis of our algorithms and suggest further research directions for improving precision by combining different approaches. We discuss the results of a large number of experiments with our analysis, which reveal context leaks in many widely used applications from the Android marketplace. This shows the practical usefulness of our technique and its superiority w.r.t. the well‐known Lint and Infer static analysis tools. We estimate the amount of memory saved by the collection of the leaks found and explain, experimentally, where programmers often go wrong and limitations of our tool. Such lessons could be used for designing of a sound or more powerful static analysis tool. This work can be considered as a practical application of software analysis techniques to solve practical problems.

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Section: Related Workmentioning

confidence: 99%

Practical static analysis of context leaks in Android applications

2018

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“…LeakDroid [27] repeatedly executes event cycles that should have a neutral effect on the resource usage, while monitoring the execution to identify potential leaks. Orion [18] performs semantics preserving mutations of a program to test the correctness of optimizing compilers.…”

Section: Related Workmentioning

confidence: 99%

“…As a supplement or alternative to manually written test suites, many automated testing techniques have been created aiming to find bugs with little or no help from the developer [3,4,6,7,12,13,14,22,23,25,27,29]. The primary advantage of such techniques is that they can, in principle, explore the state space more extensively, including the unusual event sequences.…”

Section: Introductionmentioning

confidence: 99%

Systematic execution of Android test suites in adverse conditions

Adamsen

Mezzetti

Møller

2015

Proceedings of the 2015 International Symposium on Software Testing and Analysis

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Event-driven applications, such as, mobile apps, are difficult to test thoroughly. The application programmers often put significant effort into writing end-to-end test suites. Even though such tests often have high coverage of the source code, we find that they often focus on the expected behavior, not on occurrences of unusual events. On the other hand, automated testing tools may be capable of exploring the state space more systematically, but this is mostly without knowledge of the intended behavior of the individual applications. As a consequence, many programming errors remain unnoticed until they are encountered by the users.We propose a new methodology for testing by leveraging existing test suites such that each test case is systematically exposed to adverse conditions where certain unexpected events may interfere with the execution. In this way, we explore the interesting execution paths and take advantage of the assertions in the manually written test suite, while ensuring that the injected events do not affect the expected outcome. The main challenge that we address is how to accomplish this systematically and efficiently.We have evaluated the approach by implementing a tool, Thor, working on Android. The results on four real-world apps with existing test suites demonstrate that apps are often fragile with respect to certain unexpected events and that our methodology effectively increases the testing quality: Of 507 individual tests, 429 fail when exposed to adverse conditions, which reveals 66 distinct problems that are not detected by ordinary execution of the tests.

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“…A variety of other defect patterns can be defined, based on some notion of "interesting" WTG paths and relevant operations inside the callbacks along such paths. For example, one could consider resource leaks �e.g., for heap memory, native memory, JNI references, or threads [45]) or more general typestate-like properties [10,31] that need to be tracked across sequences of callbacks. Second, the control-flow analysis could be generalized to represent multiple threads running concurrently with the main UI thread, both for general Java threads and for Android-specific constructs such as asynchronous tasks and services.…”

Section: Discussionmentioning

confidence: 99%

Static detection of energy defect patterns in Android applications

Yang

Rountev

2016

Proceedings of the 25th International Conference on Compiler Construction

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For static analysis researchers, Android software presents a wide variety of interesting challenges. The target of our work is static detection of energy-drain defects in Android applications. The management of energy-intensive resources �e.g., GPS) creates various opportunities for software defects.Our goal is to detect statically "missing deactivation" energydrain defects in the user interface of the application. First, we define precisely two patterns of run-time energy-drain behaviors, based on modeling of Android GUI control-flow paths and energy-related listener leaks along such paths. Next, we define a static detection algorithm targeting these patterns. The analysis considers valid interprocedural control-flow paths in a callback method and its transitive callees, in order to detect operations that add or remove listeners. Sequences of callbacks are then analyzed for possible listener leaks. Our evaluation considers the detection of GUI-related energy-drain defects reported in prior work, as well as new defects not discovered by prior approaches. In summary, the detection is very effective and precise, suggesting that the proposed analysis is suitable for practical use in static checking tools for Android.

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Systematic testing for resource leaks in Android applications

Cited by 45 publications

References 31 publications

Practical static analysis of context leaks in Android applications

Practical static analysis of context leaks in Android applications

Systematic execution of Android test suites in adverse conditions

Static detection of energy defect patterns in Android applications

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