Cross-Failure Bug Detection in Persistent Memory Programs
Sihang Liu, Korakit Seemakhupt, Yizhou Wei, Thomas F. Wenisch, Aasheesh Kolli, Samira Manabi Khan
摘要
Persistent memory (PM) technologies, such as Intel's Optane memory, deliver high performance, byte-addressability, and persistence, allowing programs to directly manipulate persistent data in memory without any OS intermediaries. An important requirement of these programs is that persistent data must remain consistent across a failure, which we refer to as the crash consistency guarantee. However, maintaining crash consistency is not trivial. We identify that a consistent recovery critically depends not only on the execution before the failure, but also on the recovery and resumption after failure. We refer to these stages as the pre- and post-failure execution stages. In order to holistically detect crash consistency bugs, we categorize the underlying causes behind inconsistent recovery due to incorrect interactions between the pre- and post-failure execution. First, a program is not crash-consistent if the post-failure stage reads from locations that are not guaranteed to be persisted in all possible access interleavings during the pre-failure stage -- a type of programming error that leads to a race that we refer to as a cross-failure race. Second, a program is not crash-consistent if the post-failure stage reads persistent data that has been left semantically inconsistent during the pre-failure stage, such as a stale log or uncommitted data. We refer to this type of bugs as a cross-failure semantic bug. Together, they form the cross-failure bugs in PM programs. In this work, we provide XFDetector, a tool that detects cross-failure bugs by automatically injecting failures into the pre-failure execution, and checking for cross-failure races and semantic bugs in the post-failure continuation. XFDetector has detected four new bugs in three pieces of PM software: one of PMDK's examples, a PM-optimized Redis database, and a PMDK library function.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper37
- AGAMOTTO: How Persistent is your Persistent Memory Application?Ian Neal, Ben Reeves, Ben Stoler, Andrew Quinn 等OSDI 2020 · 被引用 43 次
- Fast, flexible, and comprehensive bug detection for persistent memory programsBang Di, Jiawen Liu, Hao Chen, Dong LiASPLOS 2021 · 被引用 37 次
- PMFuzz: test case generation for persistent memory programsSihang Liu, Suyash Mahar, Baishakhi Ray, Samira Manabi KhanASPLOS 2021 · 被引用 36 次
- Jaaru: efficiently model checking persistent memory programsHamed Gorjiara, Guoqing Harry Xu, Brian DemskyASPLOS 2021 · 被引用 34 次
- BBB: Simplifying Persistent Programming using Battery-Backed BuffersMohammad A. Alshboul, Prakash Ramrakhyani, William Wang, James Tuck 等HPCA 2021 · 被引用 34 次
相关 Paper
- Yashme: detecting persistency racesHamed Gorjiara, Guoqing Harry Xu, Brian DemskyASPLOS 2022 · 被引用 18 次
- Efficiently detecting concurrency bugs in persistent memory programsZhangyu Chen, Yu Hua, Yongle Zhang, Luochangqi DingASPLOS 2022 · 被引用 11 次
- Mumak: Efficient and Black-Box Bug Detection for Persistent MemoryJoão Gonçalves, Miguel Matos, Rodrigo RodriguesEuroSys 2023 · 被引用 5 次
- Constraint Based Program Repair for Persistent Memory BugsZunchen Huang, Chao WangICSE 2024 · 被引用 3 次
- HybridPersist: A Compiler Support for User-Friendly and Efficient PM ProgrammingYiyu Zhang, Yongzhi Wang, Yanfeng Gao, Xuandong Li 等OOPSLA 2025
