VLDB 2026 Research / reviewers in the wild / expert
Xuanqing Shi
dblp:340/0136
· DBLP profile ↗
3ranked-venue papers
0as first author
3since 2021 · last 2026
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 2 · 2 since 2021Software engineering, systems software and programming languages · 2 · 2 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | TRIGFUZZ: Triggering Conditions Guided Directed Fuzzing
Nuoqi Gui, Xuanqing Shi, Chao Zhang 0008 |
SP | 5 |
| 2025 | Tracing Service Request Processing in CloudabstractABSTRACT Nowadays, more and more IT services are being hosted on cloud systems, which render cloud systems to grow into a huge complex with millions of physical servers, multi‐layer software stacks and the processing of cloud service requests across many servers and software layers. It is highly demanded for cloud service providers to have the capability of getting the knowledge on cloud service behaviour directly from the service execution instead of from people's expertise. This paper studies the problem of tracing cloud service's processing of requests across components in cloud environments and proposes cloud tracing mechanisms for this purpose. We also developed model‐based studies of our proposed mechanisms for analysing certain designs of the mechanisms. The implementation of the proposed cloud tracing is deployed onto the environments of OpenStack, Kubernetes and Hadoop, and the experiments on these environments demonstrate that our mechanisms effectively trace cloud service behaviour and generate a single complete request execution path, while without our mechanisms the cloud tracing either fails to work or results in thousands of path segments. Our mechanisms have a low performance overhead (2.3%) in the experiments. Yinqin Zhao, Long Wang 0003, Xuanqing Shi, Yong Yang 0011, Ying Li 0012, Zhengang Wang, Dongdong Shangguan |
Softw. Test. Verification Reliab. | 5 |
| 2022 | Tracing Processing of Service Requests in Cloud EnvironmentsabstractCloud computing is growingly popular for hosting IT services, and is also growing into a huge complex with millions of physical servers, multi-layer software stacks and the processing of cloud service requests across many servers and software layers. It is highly demanded for cloud service providers to have the capability of getting the knowledge on cloud service behavior directly from the service execution instead of from people's expertise. This paper studies the problem of tracing cloud services' processing of requests across components in cloud environments, and proposes cloud tracing mechanisms for this purpose. The implementation of the proposed cloud tracing is deployed onto an OpenStack cloud environment, and the experiments performed on the cloud environment shows that our mechanisms effectively trace cloud service behavior and generate a single complete request execution path, while without our mechanisms the cloud tracing either could not work or results in thousands of path segments. Our mechanisms' performance overhead is low (2.3%). Yinqin Zhao, Long Wang 0003, Xuanqing Shi, Yong Yang 0011, Ying Li 0012, Zhengang Wang, Dongdong Shangguan |
PRDC | 5 |