协同药物隔离

Aditya V. Thakur, Rathijit Sen, B. Liblit, Shan Lu
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引用次数: 14

摘要

随着多核硬件的广泛部署,编写并发程序已成为不可避免的问题。这使得修复并发错误(或药物)在现代软件系统中变得至关重要。用于查找诸如数据竞争和原子性冲突之类的问题的静态分析技术是不可扩展的,而动态方法则会导致高运行时开销。药物带来了更大的挑战,因为它们仅在内部测试期间可能不会出现的特定执行交错中显示。因此,迫切需要一种可以在部署后使用的低开销程序监视技术。我们提出合作药物分离(CCI),一种低开销的仪器技术,以分离药物的根本原因。CCI插入检测工具,通过跟踪对内存位置的连续访问是由同一个线程还是由不同的线程进行的,从而在运行时记录特定线程交错的发生情况。通过使用一种新颖的跨线程随机抽样策略,可以降低检测的开销。我们在协作Bug隔离框架之上实现了CCI。CCI正确地诊断了几个重要并发应用程序中的bug,同时只产生2- 7%的运行时开销。
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Cooperative crug isolation
With the widespread deployment of multi-core hardware, writing concurrent programs has become inescapable. This has made fixing concurrency bugs (or crugs) critical in modern software systems. Static analysis techniques to find crugs such as data races and atomicity violations are not scalable, while dynamic approaches incur high run-time overheads. Crugs pose a greater challenge since they manifest only under specific execution interleavings that may not arise during in-house testing. Thus there is a pressing need for a low-overhead program monitoring technique that can be used post-deployment. We present Cooperative Crug Isolation (CCI), a low-overhead instrumentation technique to isolate the root causes of crugs. CCI inserts instrumentation that records occurrences of specific thread interleavings at run-time by tracking whether successive accesses to a memory location were by the same thread or by distinct threads. The overhead of this instrumentation is kept low by using a novel cross-thread random sampling strategy. We have implemented CCI on top of the Cooperative Bug Isolation framework. CCI correctly diagnoses bugs in several nontrivial concurrent applications while incurring only 2--7% run-time overhead.
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