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Detecting resource leaks through dynamical mining of resource usage patterns

机译:通过动态挖掘资源使用模式来检测资源泄漏

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Resource management is crucial to software productions. Resources must be carefully acquired and released, or a resource leak might occur. For open source projects, resource leaks can be easily introduced during code check-in, and it is laborious to review, identify, report, and fix such leaks. Recently, there has been a growing interest in data mining API usage patterns to discover potential bugs such as resource leaks. However, the usage patterns mined are specific to a certain library, which cannot be applied to detect bugs in other libraries. In this paper, we present an idea called MODE, “Mine Once, Detect Everywhere”, to address the universality of such patterns, and use them to detect potential resource leaks automatically before code check-in. We propose an efficient algorithm to record the most valuable API calls that are related to resource usage during program execution, and mine resource usage patterns from the traces with a sequence miner. To verify the effectiveness of the patterns, experiments are given to use them to detect real resource leaks in large open source projects.
机译:资源管理对于软件生产至关重要。必须仔细获取和释放资源,否则可能发生资源泄漏。对于开源项目,很容易在代码检入期间引入资源泄漏,并且很难检查,识别,报告和修复此类泄漏。最近,人们对数据挖掘API使用模式越来越感兴趣,以发现潜在的错误,例如资源泄漏。但是,挖掘的使用模式特定于某个库,不能应用于检测其他库中的错误。在本文中,我们提出了一种称为MODE的想法,即“一次开采,到处检测”,以解决此类模式的普遍性,并使用它们在代码检入之前自动检测潜在的资源泄漏。我们提出了一种高效的算法来记录与程序执行过程中资源使用相关的最有价值的API调用,并使用序列挖掘器从跟踪中挖掘资源使用模式。为了验证这种模式的有效性,我们进行了实验以使用它们来检测大型开源项目中的实际资源泄漏。

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