Tuo Li 0005

dblp:150/1609-5 · DBLP profile ↗
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5ranked-venue papers
3as first author
5since 2021 · last 2024
0000-0002-2955-6788ORCID · conflict

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

Systems, architecture and hardware · 3 · 2 first-author · 3 since 2021Security and privacy · 2 · 1 first-author · 2 since 2021Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021
YearPublicationVenuePosition
2024 LR-Miner: Static Race Detection in OS Kernels by Mining Locking Rules
Tuo Li 0005, Jia-Ju Bai, Gui-Dong Han, Shi-Min Hu 0001
USENIX Security Symposium1
2024 SPATA: Effective OS Bug Detection with Summary-Based, Alias-Aware, and Path-Sensitive Typestate Analysis
abstract
The operating system (OS) is the cornerstone for computer systems. It manages hardware and provides fundamental service for user-level applications. Thus, detecting bugs in OSes is important to improve the reliability of computer systems. Static typestate analysis is a common technique for detecting various types of bugs, but it is often inaccurate or unscalable for large-size OS code, due to imprecision of identifying alias relationships as well as high costs of typestate tracking, path-feasibility validation, and inter-procedural analysis. In this article, 1 we present SPATA, a novel summary-based, alias-aware, and path-sensitive typestate analysis framework to detect OS bugs. To identify precise alias relationships in the OS code, SPATA performs a path-based alias analysis based on control-flow paths and access paths. With these alias relationships, SPATA reduces the costs of typestate tracking and path-feasibility validation, to accelerate path-sensitive typestate analysis for accurate bug detection. Moreover, SPATA uses an alias-summary-based analysis to accelerate inter-procedural bug detection, without time-consuming alias analysis across functions. We have evaluated SPATA on the Linux kernel and three popular IoT OSes, and it finds 651 real bugs with a false-positive rate of 18%. Besides, our alias-summary-based analysis achieves a 6.7x speedup in bug detection compared to non-summary-based analysis.
Tuo Li 0005, Jia-Ju Bai, Yulei Sui, Shi-Min Hu 0001
ACM Trans. Comput. Syst.1
2022 Path-sensitive and alias-aware typestate analysis for detecting OS bugs
abstract
Operating system (OS) is the cornerstone for modern computer systems. It manages devices and provides fundamental service for user-level applications. Thus, detecting bugs in OSes is important to improve reliability and security of computer systems. Static typestate analysis is a common technique for detecting different types of bugs, but it is often inaccurate or unscalable for large-size OS code, due to imprecision of identifying alias relationships as well as high costs of typestate tracking and path-feasibility validation.
Tuo Li 0005, Jia-Ju Bai, Yulei Sui, Shi-Min Hu 0001
ASPLOS1
2022 DLOS: Effective Static Detection of Deadlocks in OS Kernels
Jia-Ju Bai, Tuo Li 0005, Shi-Min Hu 0001
USENIX ATC2
2021 Static Detection of Unsafe DMA Accesses in Device Drivers
Jia-Ju Bai, Tuo Li 0005, Kangjie Lu, Shi-Min Hu 0001
USENIX Security Symposium2