Dynamic program monitoring is an effective technique for detecting bugs and security attacks in running applications. Because of the industry-wide shift to multicore chips, program monitoring tools must be extended to monitor parallel programs. Parallel programs introduce a new challenge for monitoring tools: inter-thread dependences. Existing tools assume sequential consistency and often slow down the monitored program by orders of magnitude. In this paper, we present a novel approach that avoids these pitfalls by not relying on detailed inter-thread dependences. Instead, we assume only that events in the distant past on other threads have become visible; we make no assumptions on the relative ordering of more recent events on other threads. To overcome the potential state explosion of considering all the possible orderings among recent events, we adapt two techniques from static dataflow analysis, reaching definitions and reaching expressions, to this new domain of dynamic parallel monitoring. Significant modifications to these techniques are proposed to ensure the correctness and efficiency of our approach. We prove that our approach is accurate, and sacrifices precision only due to the lack of a a relative ordering among recent events. Finally, we show how our adapted analysis can be used in two popular memory and security tools.

29 pages

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