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Wang Rui

dblp:350/0631 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0001-0343-7860ORCID · reported

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

Systems, architecture and hardware · 1 · 1 since 2021Software engineering, systems software and programming languages · 1 · 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 · 100%
Network and information security
1 paper
Systems and software security · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Systems and software security › vulnerability discovery › fuzzing
kernel fuzzing
0.912025
Snowplow: Effective Kernel Fuzzing with a Learned White-box Test Mutator · ASPLOS (2) 2025
Software testing
fuzzing
0.912025
Snowplow: Effective Kernel Fuzzing with a Learned White-box Test Mutator · ASPLOS (2) 2025
Software testing › mutation testing
program mutation
0.912025
Snowplow: Effective Kernel Fuzzing with a Learned White-box Test Mutator · ASPLOS (2) 2025
Software testing › system software testing
kernel testing
0.312025
Snowplow: Effective Kernel Fuzzing with a Learned White-box Test Mutator · ASPLOS (2) 2025

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

white-box mutation · 1.7machine learning · 1.7
YearPublicationVenuePosition
2025 Snowplow: Effective Kernel Fuzzing with a Learned White-box Test Mutator
abstract
Kernel fuzzers rely heavily on program mutation to automatically generate new test programs based on existing ones. In particular, program mutation can alter the test's control and data flow inside the kernel by inserting new system calls, changing the values of call arguments, or performing other program mutations. However, due to the complexity of the kernel code and its user-space interface, finding the effective mutation that can lead to the desired outcome such as increasing the coverage and reaching a target code location is extremely difficult, even with the widespread use of manually-crafted heuristics.
Sishuai Gong, Wang Rui, Deniz Altinbüken, Pedro Fonseca 0001, Petros Maniatis
ASPLOS (2)2