HiddenCPG: Large-Scale Vulnerable Clone Detection Using Subgraph Isomorphism of Code Property Graphs

Wi, Seongil; Woo, Sijae; Whang, Joyce Jiyoung; Son, Sooel

doi:10.1145/3485447.3512235

Cited by 9 publications

(1 citation statement)

References 48 publications

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“…• To schedule graph tasks over multiple servers (vehicles), it is necessary to solve the subgraph isomorphism problem, which is NP-complete [10]. Additionally, network dynamics such as changing topology of the MVC, varying channel quality, and uncertainties in resource supply can make the problem even more complex.…”

Section: Introductionmentioning

confidence: 99%

Graph-Represented Computation-Intensive Task Scheduling Over Air-Ground Integrated Vehicular Networks

Liwang

Gao

Hosseinalipour

et al. 2023

IEEE Trans. Serv. Comput.

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To effectively process data across a fleet of dynamic and distributed vehicles, it is crucial to implement resource provisioning techniques that provide reliable, cost-effective, and real-time computing services. This article explores resource provisioning for computation-intensive tasks over mobile vehicular clouds (MVCs). We use undirected weighted graphs (UWGs) to model both the execution of tasks and communication patterns among vehicles in a MVC. We then study low-latency and reliable scheduling of UWG tasks through a novel methodology named double-plan-promoted isomorphic subgraph search and optimization (DISCO). In DISCO, two complementary plans are envisioned to ensure effective task completion: Plan A and Plan B. Plan A analyzes the past data to create an optimal mapping (α) between tasks and the MVC in advance to the practical task scheduling. Plan B serves as a dependable backup, designed to find a feasible mapping (β) in case α fails during task scheduling due to unpredictable nature of the network. We delve into DISCO's procedure and key factors that contribute to its success. Additionally, we provide a case study that includes comprehensive comparisons to demonstrate DISCO's exceptional performance in regards to time efficiency and overhead. We further discuss a series of open directions for future research.

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Section: Introductionmentioning

confidence: 99%