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Kuei Sun

dblp:122/4854 · also Kuei Jack Sun · DBLP profile ↗
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7ranked-venue papers
5as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 5 · 3 first-authorSoftware engineering, systems software and programming languages · 2 · 2 first-authorDatabases, data management, data science and information retrieval · 2 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
4 papers
Storage systems · 89% Embedded and real-time systems · 11%
Software engineering, system software, and programming languages
3 papers
Program verification · 38% Programming languages and type systems · 35% Operating systems · 26%

Topics — the 8 heaviest of 10, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems
file systems
1.142020
Spiffy: Enabling File-System Aware Storage Applications · ACM Trans. Storage 2020
Spiffy: Enabling File-System Aware Storage Applications · FAST 2018
Recon: Verifying file system consistency at runtime · ACM Trans. Storage 2012
Storage systems › file systems
file-system metadata
0.412020
Spiffy: Enabling File-System Aware Storage Applications · ACM Trans. Storage 2020
Embedded and real-time systems › runtime monitoring
runtime verification
0.322012
Recon: Verifying file system consistency at runtime · ACM Trans. Storage 2012
Recon: verifying file system consistency at runtime · FAST 2012
Program verification › dynamic verification
runtime verification
0.112012
Recon: verifying file system consistency at runtime · FAST 2012
Storage systems
crash consistency
0.112012
Recon: Verifying file system consistency at runtime · ACM Trans. Storage 2012
Storage systems › file systems
file system consistency
0.112012
Recon: verifying file system consistency at runtime · FAST 2012
Storage systems › file systems › distributed file system
metadata consistency
0.112012
Recon: Verifying file system consistency at runtime · ACM Trans. Storage 2012
Programming languages and type systems › specification language
annotation language
0.112020
Spiffy: Enabling File-System Aware Storage Applications · ACM Trans. Storage 2020

Methods — techniques the papers use, named apart from their topics

metadata parsing · 0.9annotation language · 0.9
YearPublicationVenuePosition
2020 Spiffy: Enabling File-System Aware Storage Applications
abstract
Many file-system applications such as defragmentation tools, file-system checkers, or data recovery tools, operate at the storage layer. Today, developers of these file-system aware storage applications require detailed knowledge of the file-system format, which requires significant time to learn, often by trial and error, due to insufficient documentation or specification of the format. Furthermore, these applications perform ad-hoc processing of the file-system metadata, leading to bugs and vulnerabilities. We propose Spiffy, an annotation language for specifying the on-disk format of a file system. File-system developers annotate the data structures of a file system, and we use these annotations to generate a library that allows identifying, parsing, and traversing file-system metadata, providing support for both offline and online storage applications. This approach simplifies the development of storage applications that work across different file systems because it reduces the amount of file-system--specific code that needs to be written. We have written annotations for the Linux Ext4, Btrfs, and F2FS file systems, and developed several applications for these file systems, including a type-specific metadata corruptor, a file-system converter, an online storage layer cache that preferentially caches files for certain users, and a runtime file-system checker. Our experiments show that applications built with the Spiffy library for accessing file-system metadata can achieve good performance and are robust against file-system corruption errors.
Kuei Sun, Daniel Fryer, Russell Wang, Joseph Chu, Matthew Lakier, Angela Demke Brown, Ashvin Goel
ACM Trans. Storage1
2018 Spiffy: Enabling File-System Aware Storage Applications
Kuei Sun, Daniel Fryer, Joseph Chu, Matthew Lakier, Angela Demke Brown, Ashvin Goel
FAST1
2018 Breaking Apart the VFS for Managing File Systems
Kuei Sun, Matthew Lakier, Angela Demke Brown, Ashvin Goel
HotStorage1
2014 Robust Consistency Checking for Modern Filesystems
Kuei Sun, Daniel Fryer, Dai Qin, Angela Demke Brown, Ashvin Goel
RV1
2013 Annotation for automation: rapid generation of file system tools
abstract
Today file system tools and file-system aware storage applications are tightly coupled with file system implementations. Developing these applications is challenging because it requires detailed knowledge of the file system format, and the code for interpreting file system metadata has to be written manually. This code is complex and file-system specific, and so the application requires significant re-engineering to support different file systems.
Kuei Sun, Daniel Fryer, Angela Demke Brown, Ashvin Goel
PLOS@SOSP1
2012 Recon: verifying file system consistency at runtime
Daniel Fryer, Kuei Sun, Rahat Mahmood, Tinghao Cheng, Shaun Benjamin, Ashvin Goel, Angela Demke Brown
FAST2
2012 Recon: Verifying file system consistency at runtime
abstract
File system bugs that corrupt metadata on disk are insidious. Existing reliability methods, such as checksums, redundancy, or transactional updates, merely ensure that the corruption is reliably preserved. Typical workarounds, based on using backups or repairing the file system, are painfully slow. Worse, the recovery may result in further corruption. We present Recon, a system that protects file system metadata from buggy file system operations. Our approach leverages file systems that provide crash consistency using transactional updates. We define declarative statements called consistency invariants for a file system. These invariants must be satisfied by each transaction being committed to disk to preserve file system integrity. Recon checks these invariants at commit, thereby minimizing the damage caused by buggy file systems. The major challenges to this approach are specifying invariants and interpreting file system behavior correctly without relying on the file system code. Recon provides a framework for file-system specific metadata interpretation and invariant checking. We show the feasibility of interpreting metadata and writing consistency invariants for the Linux ext3 file system using this framework. Recon can detect random as well as targeted file-system corruption at runtime as effectively as the offline e2fsck file-system checker, with low overhead.
Daniel Fryer, Kuei Sun, Rahat Mahmood, Tinghao Cheng, Shaun Benjamin, Ashvin Goel, Angela Demke Brown
ACM Trans. Storage2