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，向最终用户提供无错误的软件变得越来越困难，这导致在用户现场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做了很多工作，但以前的大多数工作都集中在非现场诊断(即在开发站点进行诊断，有程序员参与)，因此不足以在用户站点诊断生产运行的软件故障。为了有效地解决生产运行中的故障，我们提出了一种新的方法，该方法在软件故障发生的瞬间自动执行现场软件故障诊断，并为编程人员提供关于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的隐私问题，也不会在正常执行过程中增加大量开销。为了实现这一雄心勃勃的目标，拟议的研究紧密集成了多个层面的创新：(1)低开销的操作和运行时系统支持，以捕获故障时刻，而不会在正常执行期间增加大量开销。(2)提出了一种新颖的、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型程序分析技术。(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定制诊断过程。

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.