长时间运行的应用程序的部分重播

Alvin Cheung, Armando Solar-Lezama, S. Madden
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引用次数: 16

摘要

已部署软件中的bug可能极其难以追踪。侵入式日志记录技术,比如记录所有不确定的输入,会导致大量的运行时开销。本文展示了符号分析如何用于为数据库和web服务器等长时间运行的程序重新创建路径等效执行。目标是通过允许开发人员遍历导致错误的最后几个请求或事务的执行,帮助开发人员调试此类长时间运行的程序。我们面临的挑战是,如何在不增加与基于输入日志记录或内存快照的传统重播技术相关的高运行时开销的情况下提供此功能。我们的方法通过记录关于程序执行的少量信息来实现这一点,例如所采取的分支的方向,然后使用符号分析来重建应用程序处理的最后几个输入的执行,以及这些输入执行之前的内存状态。我们在一个叫做bbr的新工具中实现了我们的技术。在本文中,我们展示了它可以用于从执行中间开始重播长时间运行的单线程程序中的错误。我们表明,bbr在程序执行期间会产生较低的记录开销(平均为10%),这比现有的重播方案要少得多。我们还展示了它可以从web服务器、数据库系统和其他常用工具中重现真正的bug。
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Partial replay of long-running applications
Bugs in deployed software can be extremely difficult to track down. Invasive logging techniques, such as logging all non-deterministic inputs, can incur substantial runtime overheads. This paper shows how symbolic analysis can be used to re-create path equivalent executions for very long running programs such as databases and web servers. The goal is to help developers debug such long-running programs by allowing them to walk through an execution of the last few requests or transactions leading up to an error. The challenge is to provide this functionality without the high runtime overheads associated with traditional replay techniques based on input logging or memory snapshots. Our approach achieves this by recording a small amount of information about program execution, such as the direction of branches taken, and then using symbolic analysis to reconstruct the execution of the last few inputs processed by the application, as well as the state of memory before these inputs were executed. We implemented our technique in a new tool called bbr. In this paper, we show that it can be used to replay bugs in long-running single-threaded programs starting from the middle of an execution. We show that bbr incurs low recording overhead (avg. of 10%) during program execution, which is much less than existing replay schemes. We also show that it can reproduce real bugs from web servers, database systems, and other common utilities.
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