The Path to Durable Linearizability
Emanuele D'Osualdo, Azalea Raad, Viktor Vafeiadis
Abstract
There is an increasing body of literature proposing new and efficient persistent versions of concurrent data structures ensuring that a consistent state can be recovered after a power failure or a crash. Their correctness is typically stated in terms of durable linearizability (DL), which requires that individual library operations appear to be executed atomically in a sequence consistent with the real-time order and, moreover, that recovering from a crash return a state corresponding to a prefix of that sequence. Sadly, however, there are hardly any formal DL proofs, and those that do exist cover the correctness of rather simple persistent algorithms on specific (simplified) persistency models. In response, we propose a general, powerful, modular, and incremental proof technique that can be used to guide the development and establish DL. Our technique is (1) general , in that it is not tied to a specific persistency and/or consistency model, (2) powerful , in that it can handle the most advanced persistent algorithms in the literature, (3) modular , in that it allows the reuse of an existing linearizability argument, and (4) incremental , in that the additional requirements for establishing DL depend on the complexity of the algorithm to be verified. We illustrate this technique on various versions of a persistent set, leading to the link-free set of Zuriel et al.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers3
- BonsaiKV: Towards Fast, Scalable, and Persistent Key-Value Stores with Tiered, Heterogeneous Memory SystemMiao Cai, Junru Shen, Yifan Yuan, Zhihao Qu et al.VLDB 2024 · 6 citations
- A Programming Model for Disaggregated Memory over CXLGal Assa, Moritz Lumme, Lucas Bürgi, Michal Friedman et al.ASPLOS 2026 · 4 citations
- Compositionality and Observational Refinement for Linearizability with CrashesArthur Oliveira Vale, Zhongye Wang, Yixuan Chen, Peixin You et al.OOPSLA 2024 · 1 citation
Builds on4
- Persistency semantics of the Intel-x86 architectureAzalea Raad, John Wickerson, Gil Neiger, Viktor VafeiadisPOPL 2020 · 61 citations
- NVTraverse: in NVRAM data structures, the destination is more important than the journeyMichal Friedman, Naama Ben-David, Yuanhao Wei, Guy E. Blelloch et al.PLDI 2020 · 52 citations
- Mirror: making lock-free data structures persistentMichal Friedman, Erez Petrank, Pedro RamalhetePLDI 2021 · 34 citations
- FliT: a library for simple and efficient persistent algorithmsYuanhao Wei, Naama Ben-David, Michal Friedman, Guy E. Blelloch et al.PPoPP 2022 · 19 citations
Related papers
- Memento: A Framework for Detectable Recoverability in Persistent MemoryKyeongmin Cho, Seungmin Jeon, Azalea Raad, Jeehoon KangPLDI 2023 · 4 citations
- MOD: Minimally Ordered Durable Datastructures for Persistent MemorySwapnil Haria, Mark D. Hill, Michael M. SwiftASPLOS 2020 · 47 citations
- DURINN: Adversarial Memory and Thread Interleaving for Detecting Durable Linearizability BugsXinwei Fu, Dongyoon Lee, Changwoo MinOSDI 2022 · 10 citations
- Constraint Based Program Repair for Persistent Memory BugsZunchen Huang, Chao WangICSE 2024 · 3 citations
- Automated Robustness Verification of Concurrent Data Structure Libraries against Relaxed Memory ModelsKartik Nagar, Anmol Sahoo, Romit Roy Chowdhury, Suresh JagannathanOOPSLA 2024 · 1 citation
