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A Hardware Approach to Detect, Expose and Tolerate High Level Data Races

机译:检测,公开和容忍高级数据争用的硬件方法

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Concurrent programs are more complex and error prone than their sequential peers, and are much harder to debug as well. High level data races (HLDR) are one of the concurrency bugs most difficult to debug. They are a class of concurrency errors that are not commonly addressed by the testing and debugging techniques and tools. HLDR result from the misdefinition of the scope of an atomic block, which should be unique but was wrongly split into two or more independent atomic blocks. Interleavings involving these misdefined atomic blocks may violate the program correctness invariants and cause the concurrent program to fail. In this work we propose a hardware module to detect, expose and tolerate HLDR in concurrent programs, with applications in both the software testing and debugging and the software deployment phases. In the detecting mode, our proposal detects HLDR with few false positives and without the overhead and intrusion of other dynamic software approaches. In the exposing mode, it "stimulates" the program to expose existing latent HLDR and trigger hidden HLDRs. Finally, in the tolerating mode, it may act as a software healing technique by inhibiting certain buggy interleavings. The results shows a reasonable performance overhead and few false positives in all modes.
机译:并发程序比顺序的同级程序更复杂且更容易出错,并且调试起来也更加困难。高级数据竞赛(HLDR)是最难调试的并发性错误之一。它们是一类并发错误,测试,调试技术和工具通常不会解决这些并发错误。 HLDR是由于原子块范围的错误定义导致的,该原子块应该是唯一的,但错误地分为两个或多个独立的原子块。涉及这些错误定义的原子块的交织可能会违反程序正确性不变性,并导致并发程序失败。在这项工作中,我们提出了一个硬件模块,用于检测,公开和容忍并发程序中的HLDR,以及在软件测试和调试以及软件部署阶段中的应用程序。在检测模式下,我们的建议以很少的误报检测HLDR,并且没有其他动态软件方法的开销和入侵。在暴露模式下,它“刺激”程序以暴露现有的潜在HLDR并触发隐藏的HLDR。最后,在容忍模式下,它可以通过抑制某些越野车交错来充当软件修复技术。结果显示了合理的性能开销,并且在所有模式下误报率均很小。

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