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User-Guided Dynamic Data Race Detection

机译:用户指导的动态数据竞争检测

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Multi-threaded programming is part of mainstream software development. It adds several issues not present on serial applications. Among the issues an important one is data races, i.e. the unsynchronized access of data by multiple threads. They are particularly hard to debug since they typically occur sporadically and often invisibly corrupt the internal state. Generally, the tool used to identify those kinds of issues is a data race analyzer. Due to the subtlety of data race bugs, the user at this point would already have tried to understand the problem using an application debugger. Debuggers offer a variety of features to analyze and modify the execution state of programs. Such features are typically not offered by data race analyzers. Integrating a data race analyzer into a debugger would improve the user workflow. This is usually prohibited by the huge performance overhead of a whole-program data race analysis. We propose in this work a method to reduce the overhead by allowing the user to define the scope of the analysis. A sufficiently narrow scope reduces the performance overhead to less than 5(times ), thus allowing its integration into a debugger. Defining the analysis scope fits naturally into the debugger workflow of focusing on one problem at a time. The work here presented has been implemented in a commercial debugger product.
机译:多线程编程是主流软件开发的一部分。它增加了串行应用程序不存在的几个问题。在这些问题中,一个重要的问题是数据争用,即多个线程对数据的不同步访问。它们特别难以调试,因为它们通常不定期地发生,并且经常不可见地破坏内部状态。通常,用于识别此类问题的工具是数据竞争分析器。由于数据争用错误的微妙之处,此时用户已经尝试使用应用程序调试器来理解问题。调试器提供了多种功能来分析和修改程序的执行状态。数据竞争分析器通常不提供此类功能。将数据竞争分析器集成到调试器中将改善用户工作流程。通常,整个程序数据争用分析的巨大性能开销禁止这样做。我们在这项工作中提出了一种通过允许用户定义分析范围来减少开销的方法。足够狭窄的范围将性能开销降低到小于5(times),从而允许将其集成到调试器中。定义分析范围自然适合于一次关注一个问题的调试器工作流程。此处介绍的工作已在商业调试器产品中实现。

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