CAREER: Building Immunity to Memory Management Bugs during Production Runs

职业：在生产运行期间建立对内存管理错误的免疫力

• 批准号: 0953759
• 负责人: Feng Qin
• 金额: $ 42万
• 依托单位: Ohio State University Research Foundation -DO NOT USE
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-03-15 至 2016-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0953759&HistoricalAwards=false
• 关键词: CAREER; Building; Immunity; Memory; Management

The widespread use of software in our society has created unprecedented demand on software availability. Unfortunately, memory management bugs, a major category of common software defects, severely affect system availability. Previous studies have shown that memory management bugs account for 43% of the reported software failures. According to the Vulnerability Notes Database maintained by the U.S. Computer Emergency Readiness Team, memory bugs are dominant in recent vulnerability reports. Memory bugs remain prevalent and challenging to handle during production runs mainly because of three reasons. First, memory bugs are deterministic, failing traditional fault tolerance methods. Second, memory bugs manifested during production runs are hard to reproduce off-site, making them difficult for diagnosis. Third, modern computing trends such as cloud computing and multi-core enable larger and more complicated software, causing memory bugs to slip into the field more easily.This project addresses the above challenges. The investigator employs a systematic approach for providing immunity to memory bugs during production runs. The main idea is to perform online diagnosis once a memory bug or failure is detected, then generate and apply runtime immune patches to the running program for surviving and preventing memory bug occurrences or failures caused by memory bugs. The research hinges on the following synergistic thrusts: (1) runtime support of diversified program execution environments for safely and efficiently surviving and preventing memory bug occurrences or failures, which addresses the determinism issue of memory bugs; (2) new algorithms for low-overhead bug diagnosis, which are applied on-site for easy reproduction of memory bugs and best exploitation of on-site bug/failure information; (3) operating system support for lightweight checkpointing and re-execution mechanisms for multi-threaded programson modern multi-core systems.

软件在我们社会中的广泛使用对软件可用性产生了前所未有的需求。不幸的是，内存管理错误，一个主要类别的常见软件缺陷，严重影响系统的可用性。以前的研究表明，内存管理错误占报告的软件故障的43%。根据美国计算机应急准备小组维护的漏洞说明数据库，内存错误在最近的漏洞报告中占主导地位。内存错误在生产运行期间仍然普遍存在，并且具有挑战性，主要原因有三个。首先，内存错误是确定性的，传统的容错方法失败。其次，在生产运行期间出现的内存错误很难在异地重现，这使得它们难以诊断。第三，云计算和多核等现代计算趋势使软件变得更大更复杂，导致内存错误更容易进入现场。本项目解决了上述挑战。调查员采用了一种系统的方法，在生产运行期间提供对内存错误的免疫力。其主要思想是一旦检测到内存错误或故障就进行在线诊断，然后生成运行时免疫补丁并将其应用于运行的程序，以生存和防止内存错误发生或由内存错误引起的故障。该研究的重点在于：（1）运行时支持多种程序执行环境，以安全有效地生存和预防内存错误的发生或故障，解决内存错误的确定性问题;（2）低开销的错误诊断新算法，应用于现场，以方便内存错误的再现和最佳利用现场错误/故障信息;（3）操作系统支持现代多核系统上的多线程程序的轻量级检查点和重新执行机制。