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1. AGAMOTTO: How Persistent is your Persistent Memory Application?

   Neal, Ian; Reeves, Ben; Stoler, Ben; Quinn, Andrew; Kwon, Youngjin; Peter, Simon; Kasikci, Baris (January 2020, 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI 20))

   null (Ed.)

   Persistent Memory (PM) can be used by applications to directly and quickly persist any data structure, without the overhead of a file system. However, writing PM applications that are simultaneously correct and efficient is challenging. As a result, PM applications contain correctness and performance bugs. Prior work on testing PM systems has low bug coverage as it relies primarily on extensive test cases and developer annotations. In this paper we aim to build a system for more thoroughly testing PM applications. We inform our design using a detailed study of 63 bugs from popular PM projects. We identify two application-independent patterns of PM misuse which account for the majority of bugs in our study and can be detected automatically. The remaining application-specific bugs can be detected using compact custom oracles provided by developers. We then present AGAMOTTO, a generic and extensible system for discovering misuse of persistent memory in PM applications. Unlike existing tools that rely on extensive test cases or annotations, AGAMOTTO symbolically executes PM systems to discover bugs. AGAMOTTO introduces a new symbolic memory model that is able to represent whether or not PM state has been made persistent. AGAMOTTO uses a state space exploration algorithm, which drives symbolic execution towards program locations that are susceptible to persistency bugs. AGAMOTTO has so far identified 84 new bugs in 5 different PM applications and frameworks while incurring no false positives. 

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2. SplitFS: Reducing Software Overhead in File Systems for Persistent Memory

   https://doi.org/10.1145/3341301.3359631  

   Rohan Kadekodi, Se Kwon (October 2020, Proceedings of the 27th ACM Symposium on Operating Systems Principles)

   We present SplitFS, a file system for persistent memory (PM) that reduces software overhead significantly compared to state-of-the-art PM file systems. SplitFS presents a novel split of responsibilities between a user-space library file system and an existing kernel PM file system. The user-space library file system handles data operations by intercepting POSIX calls, memory-mapping the underlying file, and serving the read and overwrites using processor loads and stores. Metadata operations are handled by the kernel PM file system (ext4 DAX). SplitFS introduces a new primitive termed relink to efficiently support file appends and atomic data operations. SplitFS provides three consistency modes, which different applications can choose from, without interfering with each other. SplitFS reduces software overhead by up-to 4× compared to the NOVA PM file system, and 17× compared to ext4 DAX. On a number of micro-benchmarks and applications such as the LevelDB key-value store running the YCSB benchmark, SplitFS increases application performance by up to 2× compared to ext4 DAX and NOVA while providing similar consistency guarantees. 

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3. P2CACHE: Exploring Tiered Memory for {In-Kernel} File Systems Caching

   Lin, Zhen; Xiang, Lingfeng; Rao, Jia; Lu, Hui (July 2023, 2023 USENIX Annual Technical Conference (USENIX ATC 23))

   Fast, byte-addressable persistent memory (PM) is becoming a reality in products. However, porting legacy kernel file systems to fully support PM requires substantial effort and encounters the challenge of bridging the gap between block-based access granularity and byte-addressability. Moreover, new PM-specific file systems remain far from production-ready, preventing them from being widely used. In this paper, we propose P2CACHE, a novel in-kernel caching mechanism to explore how legacy kernel file systems can effectively evolve in the face of fast, byte-addressable PM. P2CACHE exploits a read/write-distinguishable memory hierarchy upon a tiered memory system involving both PM and DRAM. P2CACHE leverages PM to serve all write requests for instant data durability and strong crash consistency while using DRAM to serve most read I/Os for high I/O performance. Further, P2CACHE employs a simple yet effective synchronization model between PM and DRAM by leveraging device-level parallelism. Our evaluation shows that P2CACHE can significantly increase the performance of legacy kernel file systems -- e.g., by 200x for RocksDB on Ext4 -- meanwhile equipping them with instant data durability and strong crash consistency, similar to PM-specialized file systems. 

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4. Enhanced File System Testing through Input and Output Coverage

   https://doi.org/10.1145/3757347.3759138  

   Liu, Yifei; Kuenning, Geoff; Parvez, Md Kamal; Smolka, Scott A; Zadok, Erez (September 2025, ACM)

   Effective file system testing relies on coverage to detect bugs and enhance reliability. We analyzed real file system bugs and found a weak correlation between code coverage, the most commonly used metric, and test effectiveness; many bugs were in covered code but remained undetected. Our study also showed that covering diverse file system inputs and outputs—system call arguments and return values—can be key to detecting the majority of observed bugs. We present input coverage and output coverage as new metrics for evaluating and improving file system testing, and have developed the IOCov framework for computing these metrics. Unlike existing system call tracers, IOCov computes coverage using only the calls relevant to testing, excluding unrelated ones that should not be counted. To demonstrate IOCov’s utility, we used it to extend the existing testing tool CrashMonkey into CM-IOCov, which achieves broader input coverage and more thorough detection of crash consistency bugs. Our experimental evaluation shows that IOCov com- putes input and output coverage accurately with minimal overhead. IOCov is applicable to different types of file system testing and can provide insights for improvement as well as identify untested cases based on coverage results. Moreover, the bugs found exclusively by CM-IOCov are 2.1 and 12.9 times more than those found exclusively by CrashMonkey on the 6.12 and 5.6 kernels, respectively, demonstrating the effectiveness of the IOCov-based coverage approach. 

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5. High Velocity Kernel File Systems with Bento

   Miller, Samantha Miller; Zhang, Kaiyuan; Chen, Mengqi; Jennings, Ryan; Chen, Ang; Zhuo, Danyang; Anderson, Thomas (February 2021, FAST'21: 19th USENIX Conference on File and Storage Technologies)

   High development velocity is critical for modern systems. This is especially true for Linux file systems which are seeing increased pressure from new storage devices and new demands on storage systems. However, high velocity Linux kernel development is challenging due to the ease of introducing bugs, the difficulty of testing and debugging, and the lack of support for redeployment without service disruption. Existing approaches to high-velocity development of file systems for Linux have major downsides, such as the high performance penalty for FUSE file systems, slowing the deployment cycle for new file system functionality. We propose Bento, a framework for high velocity development of Linux kernel file systems. It enables file systems written in safe Rust to be installed in the Linux kernel, with errors largely sandboxed to the file system. Bento file systems can be replaced with no disruption to running applications, allowing daily or weekly upgrades in a cloud server setting. Bento also supports userspace debugging. We implement a simple file system using Bento and show that it performs similarly to VFS-native ext4 on a variety of benchmarks and outperforms a FUSE version by 7x on 'git clone'. We also show that we can dynamically add file provenance tracking to a running kernel file system with only 15ms of service interruption. 

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