Race detection for event-driven mobile applications

Hsiao, Chun-Hung; Yu, Jie; Narayanasamy, Satish; Kong, Ziyun; Pereira, Cristiano; Pokam, Gilles; Chen, Peter M.; Flinn, Jason

doi:10.1145/2594291.2594330

Cited by 78 publications

(39 citation statements)

References 18 publications

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“…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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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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“…Penelope doesn't use concolic execution. Recent papers [51,33,40] show how to detect data races in event-driven and reactive programs; their techniques might also be useful for deadlock detection in such programs.…”

Section: Related Workmentioning

confidence: 99%

Sherlock: scalable deadlock detection for concurrent programs

Eslamimehr

Palsberg

2014

Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering

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We present a new technique to find real deadlocks in concurrent programs that use locks. For 4.5 million lines of Java, our technique found almost twice as many real deadlocks as four previous techniques combined. Among those, 33 deadlocks happened after more than one million computation steps, including 27 new deadlocks. We first use a known technique to find 1275 deadlock candidates and then we determine that 146 of them are real deadlocks. Our technique combines previous work on concolic execution with a new constraint-based approach that iteratively drives an execution towards a deadlock candidate.

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“…State-of-the-art To address this challenge in the setting of event-driven applications, recent works have proposed mechanisms for going beyond ordinary testing and detecting sources of nondeterminism where event handlers may interfere and can execute in any order [13,14,18,26,27]. While detecting interference is a useful building block, it still lacks essential analysis capabilities.…”

Section: Introductionmentioning

confidence: 99%

Stateless model checking of event-driven applications

Jensen

Møller

Raychev

et al. 2015

Proceedings of the 2015 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applicatio

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Modern event-driven applications, such as, web pages and mobile apps, rely on asynchrony to ensure smooth end-user experience. Unfortunately, even though these applications are executed by a single event-loop thread, they can still exhibit nondeterministic behaviors depending on the execution order of interfering asynchronous events. As in classic shared-memory concurrency, this nondeterminism makes it challenging to discover errors that manifest only in specific schedules of events.In this work we propose the first stateless model checker for event-driven applications, called R4. Our algorithm systematically explores the nondeterminism in the application and concisely exposes its overall effect, which is useful for bug discovery. The algorithm builds on a combination of three key insights: (i) a dynamic partial order reduction (DPOR) technique for reducing the search space, tailored to the domain of event-driven applications, (ii) conflict-reversal bounding based on a hypothesis that most errors occur with a small number of event reorderings, and (iii) approximate replay of event sequences, which is critical for separating harmless from harmful nondeterminism.We instantiate R4 for the domain of client-side web applications and use it to analyze event interference in a number of real-world programs. The experimental results indicate that the precision and overall exploration capabilities of our system significantly exceed that of existing techniques.

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Race detection for event-driven mobile applications

Cited by 78 publications

References 18 publications

Systematic execution of Android test suites in adverse conditions

Systematic execution of Android test suites in adverse conditions

Sherlock: scalable deadlock detection for concurrent programs

Stateless model checking of event-driven applications

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