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樓主: Considerate
31#
發(fā)表于 2025-3-26 22:39:20 | 只看該作者
32#
發(fā)表于 2025-3-27 03:16:29 | 只看該作者
https://doi.org/10.1007/978-3-662-59230-4tion results in communication delays among agents that have to be adequately taken into account by software models to avoid race conditions. However, engineering DCPSs at a higher level of detail by incorporating communication delays explicitly inflates model size and impedes analysis..In this paper
33#
發(fā)表于 2025-3-27 09:20:08 | 只看該作者
https://doi.org/10.1007/978-3-662-62074-8es when it comes to properly securing the APIs against the usual web application security risks, e.g., broken access control. A prominent security testing approach is taint analysis, which traces tainted, i.e., security-relevant, data from sources (where tainted data is inserted) to sinks (where the
34#
發(fā)表于 2025-3-27 11:28:36 | 只看該作者
35#
發(fā)表于 2025-3-27 17:21:45 | 只看該作者
36#
發(fā)表于 2025-3-27 17:47:28 | 只看該作者
37#
發(fā)表于 2025-3-28 01:10:53 | 只看該作者
38#
發(fā)表于 2025-3-28 04:27:15 | 只看該作者
39#
發(fā)表于 2025-3-28 07:56:46 | 只看該作者
40#
發(fā)表于 2025-3-28 11:32:24 | 只看該作者
Checking Transaction Isolation Violations Using Graph Queries uses graph databases and queries to detect isolation violations expressed as anti-patterns in transactional dependency graphs. We implement the approach on top of the popular ArangoDB and Neo4j graph databases and show its efficiency through an experimental analysis of real executions of ArangoDB as a system under test.
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