发表机构
Karlsruhe Institute of Technology; Karlsruhe University of Applied Sciences（卡尔斯鲁厄理工学院; 卡尔斯鲁厄应用科学大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出基于模型的CAN流量生成与操纵工具CANcept，通过流量调度模型和DBC通信模型实现精确时序控制，初步评估显示低偏差和高稳定性。
AI 中文摘要
测试基于控制器局域网（CAN）的软件中与时间相关的安全属性，需要对传输数据和通信时序进行精确控制。现有的开源工具通常以低级脚本编码此类场景，使其难以维护和演进。我们提出了\ oolName{}，一个开源的基于模型的工具，用于指定、生成、重放和操纵CAN流量。流量调度模型（TSM）定义消息时序和内容转换，而基于DBC的通信模型（DCM）定义消息级流量与CAN帧之间的编码和解码。\ oolName{}在一个执行机制中结合了两种模型，用于生成和操纵的流量，包括转换轨迹的重放。初步评估表明，\ oolName{}实现了指定的场景，在高流量速率下具有低时序偏差和稳定执行。
英文摘要
Testing timing-related safety properties of Controller Area Network (CAN)-based software requires precise control over transmitted data and communication timing. Existing open-source tools typically encode such scenarios in low-level scripts, making them difficult to maintain and evolve. We present \toolName{}, an open-source model-based tool for specifying, generating, replaying, and manipulating CAN traffic. A traffic schedule model (TSM) defines message timing and content transformations, and a DBC-based communication model (DCM) defines encoding and decoding between message-level traffic and CAN frames. \toolName{} combines both models in one execution mechanism for generated and manipulated traffic, including replay of transformed traces. A preliminary evaluation indicates that \toolName{} realizes the specified scenarios, with low timing deviation and stable execution under elevated traffic rates.
Journal refMODELS 2026
