CSR---PDOS: Online Production-Run Software Failure Diagnosis at the User Site

随着软件系统在规模、复杂性和成本上的增长，向最终用户交付无缺陷软件变得越来越困难，这导致在用户站点的生产运行期间出现许多软件故障。虽然在软件故障诊断方面已经进行了很多工作，但大多数以前的工作集中在非现场诊断（即在程序员参与的开发现场进行诊断），因此不足以在用户现场诊断生产运行的软件故障。为了有效地解决生产运行故障，我们提出了一种新颖的方法，在软件故障发生的那一刻自动执行现场软件故障诊断，并为程序员提供有关所发生故障的详细诊断报告，包括错误类型，错误位置，可能的根本原因，故障传播链，故障触发输入，故障触发执行环境，潜在的临时修复等，而不会违反用户？S隐私问题或在正常执行期间施加大量开销。为了实现这一宏伟目标，本文提出的研究将多个层面的创新紧密结合在一起：(1)低开销的操作和运行时系统支持，在正常执行过程中不施加大开销的情况下捕获故障时刻。(2)一种新颖的、可扩展的、可定制的、类似人类的故障诊断协议。(3)专门为现场故障诊断设计的新颖程序分析技术。(4)利用现有的和新兴的硬件支持和简单的硬件扩展来减少开销。(5)基于库的API，允许应用程序在必要时控制或自定义诊断过程。

As software systems have grown in size, complexity and cost, it has become increasingly difficult to deliver software bug-free to end users, which result in many software failures during production runs at the user site. While much work has been conducted on software failure diagnosis, most previous work focuses on off-site diagnosis (i.e. diagnosis at the development site with involvement of programmers) and thereby is insufficient to diagnose production-run software failure at the user site. To effectively address production-run failures, we propose a novel approach that automatically performs on-site software failure diagnosis right at the moment of a software failure and provide programmers a detailed diagnosis report regarding the occurred failure, including bug type, bug location, likely root cause, fault propagation chain, failure-triggering input, failure-triggering execution environment, potential temporal fixes, etc, without violating user?s privacy concerns or imposing large overhead during normal execution. To achieve the ambitious goal, the proposed research tightly integrates innovations from multiple layers: (1) Low-overhead operating and run-time system support to capture the failure moment without imposing large overhead during normal execution. (2) A novel, extensible, customizable, human-like failure diagnosis protocol. (3) Novel program analysis techniques that are specifically designed for on-site failure diagnosis. (4) Leverage existing and emerging hardware support and simple hardware extensions to reduce overhead.(5) A library-based API to allow applications to control or customize the diagnosis process if necessary.