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Si-Miao Gao

dblp:412/6202 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0001-8619-7152ORCID · reported

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

Security and privacy · 1 · 1 first-author · 1 since 2021

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.

Software engineering, system software, and programming languages
1 paper
Software testing · 61% Concurrent programming · 30% Debugging and program repair · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Concurrent programming
concurrency bugs
0.912025
Detecting Lifecycle-Related Concurrency Bugs in ROS Programs via Coverage-Guided Fuzzing · IEEE Trans. Inf. Forensics Secur. 2025
Software testing › fuzzing
coverage-guided fuzzing
0.912025
Detecting Lifecycle-Related Concurrency Bugs in ROS Programs via Coverage-Guided Fuzzing · IEEE Trans. Inf. Forensics Secur. 2025
Software testing
fuzzing
0.912025
Detecting Lifecycle-Related Concurrency Bugs in ROS Programs via Coverage-Guided Fuzzing · IEEE Trans. Inf. Forensics Secur. 2025
Debugging and program repair
bug reproduction
0.312025
Detecting Lifecycle-Related Concurrency Bugs in ROS Programs via Coverage-Guided Fuzzing · IEEE Trans. Inf. Forensics Secur. 2025

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

lifecycle-aware fuzzing · 0.9delay injection · 0.9coverage-guided fuzzing · 0.9
YearPublicationVenuePosition
2025 Detecting Lifecycle-Related Concurrency Bugs in ROS Programs via Coverage-Guided Fuzzing
abstract
Robot Operating System (ROS) is very popular in robotic software development. To ease the process management of ROS programs, ROS provides a speciallifecyclemechanism that can conveniently manage the state of each running process, which often involves resource allocation, initialization, and release; and this mechanism has been widely used in real-world ROS programs. However, due to code concurrency of ROS programs, a lifecycle-related function is inevitably concurrently executed with other functions, introducing the security risk of dangerous concurrency bugs involving null-pointer dereference and use after free. Due to the non-determinism of thread scheduling, these concurrency bugs are difficult to find and reproduce. In this paper, we design and implement a new coverage-guided fuzzing framework named ROCF, which can effectively detect and reproduce lifecycle-related concurrency bugs in ROS programs, with two novel techniques. First, we propose alifecycle-aware fuzzing approachthat useslifecycle pair sequenceas a new coverage metric to effectively describe lifecycle-related thread interleavings, for input-mutation guidance of ROS concurrency fuzzing. Second, we propose aheuristic-based reproducing methodthat identifies minimal input sequences that can stably and efficiently reproduce the found concurrency bugs, with strategical input pruning and delay injection. We evaluate ROCF on eight popular robotic programs in ROS2, and it finds 32 new and real concurrency bugs, all of which have been confirmed by ROS developers, and 19 have been assigned CVE IDs.
Si-Miao Gao, Pengcheng Wang 0003, Jia-Ju Bai, Jia-Wei Yu, Haizhou Wang 0001
IEEE Trans. Inf. Forensics Secur.1