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.

The Past, Present, and Future of Storage Technologies (part 2 of 2)Any good research project begins with a "literature review"-a process of looking for papers relevant to a topic of interest, reviewing them to identify those more useful while discarding the rest, then looking for more papers, and repeating this process over and over until you feel you have reached some saturation point.That is the point when you're coming up against the same papers you have seen already (which we like to call the "transitive closure" point).This review stage is fairly time-consuming but also critical; in fact, many research papers get rejected for neglecting to cite important related work.Similarly, practitioners may run into roadblocks that they could have avoided if they had been aware of all the existing literature.So, are you a new graduate student or an employee at a company who is interested in innovating in a given storage technology?Do you wish you could find a single publication that would summarize (almost) everything there is to know about a specific technology?If so, this Special Issue (both parts) is hopefully for you because, unlike conference papers, our journal articles have no page limits and thus allow authors to discuss any technology with as much detail as needed and include a comprehensive bibliography for those interested in more.Incidentally, we found out that survey papers tend to get well cited and received.We believe this is because they become a "go to" source on a topic, thus saving the readers from having to read and cite many other papers.Authors of survey papers may see their articles cited over and over.In 2023, TOS's Editor-in-Chief ( EiC ) reached out to a few senior people to brainstorm ideas for special issues.Because putting together a special issue is a huge task, he recruited several Associate Editors (AEs) to help.We settled on an idea particularly suitable for journals: survey papers.And we decided to focus on the bottom of the storage stack: storage technologies and media.We also debated whether we should focus on futuristic technologies, current, or past ones.In the end, we opted to include everything: all storage technologies, regardless of their age or maturity, can teach us something useful.Normally, TOS authors submit their full manuscript for review.However, because this special issue's survey nature would likely mean longer papers, we wanted to provide better direction to authors.So, we posted a CFP asking the prospective authors to submit a short one-page abstract.We provided guidance to prospective authors as to what makes a good survey paper.Specifically, authors would have to survey many related papers in their chosen area, so as to make their survey the most comprehensive paper on the topic to date.Secondly, it was not enough to just summarize past papers; authors also needed to provide insight into why and how a given technology evolved over the years, and where it might go in the future.

We present a comprehensive pipeline, integrated with a visual analytics system called GapMiner, capable of exploring and exploiting untapped opportunities within the empty regions of high-dimensional datasets. Our approach utilizes a novel Empty-Space Search Algorithm (ESA) to identify the center points of these uncharted voids, which represent reservoirs for potentially valuable new configurations. Initially, this process is guided by user interactions through GapMiner, which visualizes Empty-Space Configurations (ESCs) within the context of the dataset and allows domain experts to explore and refine ESCs for subsequent validation in domain experiments or simulations. These activities iteratively enhance the dataset and contribute to training a connected deep neural network (DNN). As training progresses, the DNN gradually assumes the role of identifying and validating high-potential ESCs, reducing the need for direct user involvement. Once the DNN achieves sufficient accuracy, it autonomously guides the exploration of optimal configurations by predicting performance and refining configurations through a combination of gradient ascent and improved empty-space searches. Domain experts were actively involved throughout the system's development. Our findings demonstrate that this methodology consistently generates superior novel configurations compared to conventional randomization-based approaches. We illustrate its effectiveness in multiple case studies with diverse objectives.

File systems need testing to discover bugs and to help ensure reliability. Many file system testing tools are evaluated based on their code coverage. We analyzed recently reported bugs in Ext4 and BtrFS and found a weak correlation between code coverage and test effectiveness: many bugs are missed because they depend on specific inputs, even though the code was covered by a test suite. Our position is that coverage of system call inputs and outputs is critically important for testing file systems. We thus suggest input and output coverage as criteria for file system testing, and show how they can improve the effectiveness of testing. We built a prototype called IOCov to evaluate the input and output coverage of file system testing tools. IOCov identified many untested cases (specific inputs and outputs or ranges thereof) for both CrashMonkey and xfstests. Additionally, we discuss a method and associated metrics to identify over- and under-testing using IOCov.

Simulating storage cache hierarchies enables efficient exploration of their configuration space, including diverse topologies, parameters and policies, and devices with varied performance characteristics, while avoiding expensive physical experiments. Miss Ratio Curves (MRCs) efficiently characterize the performance of a cache over a range of cache sizes. These useful tools reveal “key points” for cache simulation, such as knees in the curve that immediately follow sharp cliffs. Unfortunately, there are no automated techniques for efficiently finding key points in MRCs, and the cross-application of existing knee-detection algorithms yields inaccurate results. We present a multi-stage framework that identifies key points in any MRC, for both stack-based (e.g., LRU) and more sophis-ticated eviction algorithms (e.g., ARC). Our approach quickly locates candidates using efficient hash-based sampling, curve simplification, knee detection, and novel post-processing filters. We introduce Z-Method, a new multi-knee detection algorithm that employs statistical outlier detection to choose promising points robustly and efficiently. We evaluate our framework against seven other knee-detection algorithms, using both ARC and LRU MRCs from 106 diverse real-world workloads, and apply it to identify key points in multi-tier MRCs. Compared to naive approaches, our framework reduces the total number of points needed to accurately identify the best two-tier cache hierarchies by an average factor of approximately$5.5\times$for ARC and$7.7\times$for LRU.

Parallel coordinate plots (PCPs) have been widely used for high-dimensional (HD) data storytelling because they allow for presenting a large number of dimensions without distortions. The axes ordering in PCP presents a particular story from the data based on the user perception of PCP polylines. Existing works focus on directly optimizing for PCP axes ordering based on some common analysis tasks like clustering, neighborhood, and correlation. However, direct optimization for PCP axes based on these common properties is restrictive because it does not account for multiple properties occurring between the axes, and for local properties that occur in small regions in the data. Also, many of these techniques do not support the human-in-the-loop (HIL) paradigm, which is crucial (i) for explainability and (ii) in cases where no single reordering scheme fits the users' goals. To alleviate these problems, we present PC-Expo, a real-time visual analytics framework for all-in-one PCP line pattern detection and axes reordering. We studied the connection of line patterns in PCPs with different data analysis tasks and datasets. PC-Expo expands prior work on PCP axes reordering by developing real-time, local detection schemes for the 12 most common analysis tasks (properties). Users can choose the story they want to present with PCPs by optimizing directly over their choice of properties. These properties can be ranked, or combined using individual weights, creating a custom optimization scheme for axes reordering. Users can control the granularity at which they want to work with their detection scheme in the data, allowing exploration of local regions. PC-Expo also supports HIL axes reordering via local-property visualization, which shows the regions of granular activity for every axis pair. Local-property visualization is helpful for PCP axes reordering based on multiple properties, when no single reordering scheme fits the user goals. A comprehensive evaluation was done with real users and diverse datasets confirm the efficacy of PC-Expo in data storytelling with PCPs.

No abstract available.

Developing and maintaining a file system is time-consuming, typically requiring years of effort. Developers often test compliance with APIs such as POSIX with hand-written regression suites that, alas, examine only a fraction of a file system's state space. Conversely, formal model checking can explore vast state spaces efficiently, increasing confidence in the file system's implementation. Yet model checking is not currently part of file system development. Our position is that file systems should be designed a priori to facilitate model checking. To this end, we introduce MCFS, an architecture for efficient and comprehensive file-system model checking. MCFS relies on two new APIs that save and restore a file system's in-memory and on-disk state. We describe our earlier attempts at model-checking file systems, including unsuccessful or inefficient ones. Those attempts led us to develop VeriFS, which implements the new APIs. We illustrate MCFS's model-checking principles with VeriFS, a FUSE-based file system we were able to quickly develop with MCFS's help.

Modern applications use storage systems in complex and often surprising ways. Tracing system calls is a common approach to understanding applications' behavior, allowing offline analysis and enabling replay in other environments. But current system-call tracing tools have drawbacks: (1) they often omit some information---such as raw data buffers---needed for full analysis; (2) they have high overheads; (3) they often use non-portable trace formats; and (4) they may not offer useful and scalable analysis and replay tools.

Deduplication has become essential in disk-based backup systems, but there have been few long-term studies of backup workloads. Most past studies either were of a small static snapshot or covered only a short period that was not representative of how a backup system evolves over time. For this article, we first collected 21 months of data from a shared user file system; 33 users and over 4,000 snapshots are covered. We then analyzed the dataset, examining a variety of essential characteristics across two dimensions: single-node deduplication and cluster deduplication. For single-node deduplication analysis, our primary focus was individual-user data. Despite apparently similar roles and behavior among all of our users, we found significant differences in their deduplication ratios. Moreover, the data that some users share with others had a much higher deduplication ratio than average. For cluster deduplication analysis, we implemented seven published data-routing algorithms and created a detailed comparison of their performance with respect to deduplication ratio, load distribution, and communication overhead. We found that per-file routing achieves a higher deduplication ratio than routing by super-chunk (multiple consecutive chunks), but it also leads to high data skew (imbalance of space usage across nodes). We also found that large chunking sizes are better for cluster deduplication, as they significantly reduce data-routing overhead, while their negative impact on deduplication ratios is small and acceptable. We draw interesting conclusions from both single-node and cluster deduplication analysis and make recommendations for future deduplication systems design.

Modern systems use networks extensively, accessing both services and storage across local and remote networks. Latency is a key performance challenge, and packing multiple small operations into fewer large ones is an effective way to amortize that cost, especially after years of significant improvement in bandwidth but not latency. To this end, the NFSv4 protocol supports a compounding feature to combine multiple operations. Yet compounding has been underused since its conception because the synchronous POSIX file-system API issues only one (small) request at a time. We propose vNFS , an NFSv4.1-compliant client that exposes a vectorized high-level API and leverages NFS compound procedures to maximize performance. We designed and implemented vNFS as a user-space RPC library that supports an assortment of bulk operations on multiple files and directories. We found it easy to modify several UNIX utilities, an HTTP/2 server, and Filebench to use vNFS. We evaluated vNFS under a wide range of workloads and network latency conditions, showing that vNFS improves performance even for low-latency networks. On high-latency networks, vNFS can improve performance by as much as two orders of magnitude.

No abstract available.

Deduplication has become essential in disk-based backup systems, but there have been few long-term studies of backup workloads. Most past studies either were of a small static snapshot or covered only a short period that was not representative of how a backup system evolves over time. For this paper, we collected 21 months of data from a shared user file system; 33 users and over 4,000 snapshots are covered. We analyzed the data set for a variety of essential characteristics. However, our primary focus was individual user data. Despite apparently similar roles and behavior in all of our users, we found significant differences in their deduplication ratios. Moreover, the data that some users share with others had a much higher deduplication ratio than average. We analyze this behavior and make recommendations for future deduplication systems design.

One important aspect of privacy is the ability to securely delete sensitive data from electronic storage in such a way that it cannot be recovered; we call this action secure deletion . Short of physically destroying the entire storage medium, existing software secure-deletion solutions tend to be piecemeal at best -- they may only work for one type of storage or file system, may force the user to delete all files instead of selected ones, may require the added complexities of encryption and key storage, may require extensive changes and additions to the computer's operating system or storage firmware, and may not handle system crashes gracefully. We present TrueErase, a holistic secure-deletion framework for individual systems that contain sensitive data. Through design, implementation, verification, and evaluation on both a hard drive and NAND flash, TrueErase shows that it is possible to construct a per-file, secure-deletion framework that can accommodate different storage media and legacy file systems, require limited changes to legacy systems, and handle common crash scenarios. TrueErase can serve as a building block by cryptographic systems that securely delete information by erasing encryption keys. The overhead is dependent on spatial locality, number of sensitive files, and workload (computational- or I/O-bound).

The popular Network File System (NFS) protocol is 30 years old. The latest version, NFSv4, is more than ten years old but has only recently gained stability and acceptance. NFSv4 is vastly different from its predecessors: it offers a stateful server, strong security, scalability/WAN features, and callbacks, among other things. Yet NFSv4's efficacy and ability to meet its stated design goals had not been thoroughly studied until now. This paper compares NFSv4.1's performance with NFSv3 using a wide range of micro- and macro-benchmarks on a testbed configured to exercise the core protocol features. We (1) tested NFSv4's unique features, such as delegations and statefulness; (2) evaluated performance comprehensively with different numbers of threads and clients, and different network latencies and TCP/IP features; (3) found, fixed, and reported several problems in Linux's NFSv4.1 implementation, which helped improve performance by up to 11X; and (4) discovered, analyzed, and explained several counter-intuitive results. Depending on the workload, NFSv4.1 was up to 67\% slower than NFSv3 in a low-latency network, but exceeded NFSv3's performance by up to 2.9X in a high-latency environment. Moreover, NFSv4.1 outperformed NFSv3 by up to 172X when delegations were used.

In this panel, we will address questions regarding the development and execution of one type of industry-academic collaboration - corporate-sponsored projects. As representatives of programs at both public and private institutions, we will address a set of questions related to these programs. We have prepared an initial list that will be augmented with questions submitted and voted on by conference participants in advance of the session. After we have presented our prepared responses, the balance of the session will be dedicated to open discussion with audience members.

The ability to securely delete sensitive data from electronic storage is becoming important. However, current per-file deletion solutions tend to be limited to a segment of the operating system's storage data path or specific to particular file systems or storage media.

This paper presents a thorough evaluation of CS for Scientists, a CS 1 course designed to provide future scientists with an overview of the discipline. The course takes a breadth-first approach that leverages its students' interest and experience in science, mathematics, and engineering. In contrast to many other styles of CS 1, this course does not presume that its students will study more computer science, but it does seek to prepare them should they choose to. We summarize the past year's worth of assessments of student learning, retention, and affect -- with particular attention paid to women's voices. Where possible, we contrast these student measures with those from a traditional, imperative-first CS1 that this new course replaced. The data thus far suggest that CS for Scientists significantly improves students' understanding of CS, its applications, and practice.

This paper describes an introductory CS course designed to provide future scientists with a one-semester overview of the discipline. The course takes a breadth-first approach that leverages its students' interest and experience in science, mathematics, and engineering. In contrast to many other styles of CS 1, this course does not presume that its students will study more computer science, but it does seek to prepare them should they choose to do so. In addition to describing the curriculum and resources, we summarize our preliminary assessments of this course and a comparison with the more traditional, imperative-first introduction it replaced. The data thus far suggest that this CS for Scientists course improves our students' understanding of CS, its applications, and practice.

Reducing power consumption for server-class computers is important, since increased energy usage causes more heat dissipation, greater cooling requirements, reduced computational density, and higher operating costs. For a typical data center, storage accounts for 27% of energy consumption. Conventional server-class RAIDs cannot easily reduce power because loads are balanced to use all disks, even for light loads. We have built the power-aware RAID (PARAID), which reduces energy use of commodity server-class disks without specialized hardware. PARAID uses a skewed striping pattern to adapt to the system load by varying the number of powered disks. By spinning disks down during light loads, PARAID can reduce power consumption, while still meeting performance demands, by matching the number of powered disks to the system load. Reliability is achieved by limiting disk power cycles and using different RAID encoding schemes. Based on our five-disk prototype, PARAID uses up to 34% less power than conventional RAIDs while achieving similar performance and reliability.

Modern file systems assume the use of disk, a system-wide performance bottleneck for over a decade. Current disk caching and RAM file systems either impose high overhead to access memory content or fail to provide mechanisms to achieve data persistence across reboots.The Conquest file system is based on the observation that memory is becoming inexpensive, which enables all file system services to be delivered from memory, except for providing large storage capacity. Unlike caching, Conquest uses memory with battery backup as persistent storage, and provides specialized and separate data paths to memory and disk. Therefore, the memory data path contains no disk-related complexity. The disk data path consists of optimizations only for the specialized disk usage pattern.Compared to a memory-based file system, Conquest incurs little performance overhead. Compared to several disk-based file systems, Conquest achieves 1.3x to 19x faster memory performance, and 1.4x to 2.0x faster performance when exercising both memory and disk. Conquest realizes most of the benefits of persistent RAM at a fraction of the cost of a RAM-only solution. It also demonstrates that disk-related optimizations impose high overheads for accessing memory content in a memory-rich environment.

No abstract available.

A number of mobile computing systems have used the technique of hoarding, which allows a mobile device to store a chosen subset of known files, to give disconnected users the illusion of a complete filesystem in the presence of limited storage. We undertook an extensive and detailed simulation study of the parameters of a well-known hoarding system, seer, in an attempt to discover the parameters that would produce the best performance. To our surprise, we discovered that the best parameter combinations were those that completely disabled seer's complex clustering methods, reverting the system instead to a modified form of LRU hoarding. We discuss the experiments and our results, and propose designs for future systems and directions for future research.

Summary form only given. The Conquest file system is designed to provide a transition from disk- to persistent-RAM-based storage. Initially, we assume 2 to 4 Gbytes of persistent RAM and the popular single-user desktop environment. Unlike other memory file systems, Conquest can incrementally assume more responsibility for in-core storage as memory prices decline. The Conquest approach realizes most of the benefits of persistent-RAM-based file systems before persistent RAM becomes cheaply abundant. Conquest also benefits from the removal of disks as the primary storage by identifying disk-related complexities and isolating them from the critical path where possible. The Conquest prototype is operational under Linux 2.4.2. It is POSIX compliant and supports both in-core and on-disk storage.

This research proposes and tests an approach to engineering distributed file systems that are aimed at wide-scale, Internet-based use. The premise is that replication is essential to deliver performance and availability, yet the traditional conservative replica consistency algorithms do not scale to this environment. Our Ficus replicated file system uses a single-copy availability, optimistic update policy with reconciliation algorithms that reliably detect concurrent updates and automatically restore the consistency of directory replicas. The system uses the peer-to-peer model in which all machines are architectural equals but still permits configuration in a client-server arrangement where appropriate. Ficus has been used for six years at several geographically scattered installations. This paper details and evaluates the use of optimistic replica consistency, automatic update conflict detection and repair, the peer-to-peer (as opposed to client-server) interaction model, and the stackable file system architecture in the design and construction of Ficus. The paper concludes with a number of lessons learned from the experience of designing, building, measuring, and living with an optimistically replicated file system. © 1998 John Wiley & Sons, Ltd.

A common problem facing mobile computing is &connected operation, or computing in the absence of a network.Hoarding eases disconnected operation by selecting a subset of the user's files forlocal storage.We describe a hoarding system that can operate without user intervention, by observing user activity and predicting future needs.The system calculates a new measure, semantic distance, between individual liles, and uses this to feed a clustering algorithm that chooses which files should be hoarded.A separatereplication system manages the actual transport of data; any of a number of replication systems may be used.We discuss practical problems encountered in the real world and present usage statistics showing that our system outperforms previous approaches by factors that can exceed 1O:l.

Abstract Kitrace is a software tool that allows dynamic interactive measurement of UNIX kernel performance to much greater precision than that available from kernel profiling. Developers can measure, to microsecond resolution, the time required by a complex kernel activity, including time spent waiting for I/O activity or user processes. Kitrace has also proven useful for debugging, especially in situations where traditional breakpointing would be undesirable or would change the behavior of the kernel.