BackgroundSystems-of-systems (SoS) are alliances of independent and interoperable software-intensive systems. SoS often support critical domains, being required to exhibit a reliable operation, specially because people’s safety relies on their services. In this direction, simulations enable the validation of different operational scenarios in a controlled environment, allowing a benchmarking of its response as well as revealing possible breaches that could lead to failures. However, simulations are traditionally manual, demanding a high level of human intervention, being costly and error-prone. A stimuli generator could aid in by continuously providing data to trigger a SoS simulation and maintaining its operation.MethodsWe established a model-based approach termed Stimuli-SoS to support the creation of stimuli generators to be used in SoS simulations. Stimuli-SoS uses software architecture descriptions for automating the creation of such generators. Specifically, this approach transforms SoSADL, a formal architectural description language for SoS, into dynamic models expressed in DEVS, a simulation formalism. We carried out a case study in which Stimuli-SoS was used to automatically produce stimuli generators for a simulation of a flood monitoring SoS.ResultsWe run simulations of a SoS architectural configuration with 69 constituent systems, i.e., 42 sensors, 9 crowdsourcing systems, and 18 drones. Stimuli generators were automatically generated for each type of constituent. These stimuli generators were capable of receiving the input data from the database and generating the expected stimuli for the constituents, allowing to simulate constituent systems interoperations into the flood monitoring SoS. Using Stimuli-SoS, we simulated 38 days of flood monitoring in little more than 6 h. Stimuli generators correctly forwarded data to the simulation, which was able to reproduce 29 flood alerts triggered by the SoS during a flooding event. In particular, Stimuli-SoS is almost 65 times more productive than a manual approach to producing data for the same type of simulation.ConclusionsOur approach succeeded in automatically deriving a functional stimuli generator that can reproduce environmental conditions for simulating a SoS. In particular, we presented new contributions regarding productivity and automation for the use of a model-based approach in SoS engineering.

中文翻译：

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Stimuli-SoS：一种基于模型的方法，用于推导出用于系统间软件架构模拟的刺激生成器

背景系统系统 (SoS) 是独立且可互操作的软件密集型系统的联盟。SoS 通常支持关键域，需要表现出可靠的操作，特别是因为人们的安全依赖于他们的服务。在这个方向上，模拟能够在受控环境中验证不同的操作场景，允许对其响应进行基准测试，并揭示可能导致故障的违规行为。然而，模拟传统上是手动的，需要高水平的人工干预，成本高昂且容易出错。刺激生成器可以通过持续提供数据来触发 SoS 模拟并维持其运行来提供帮助。方法我们建立了一种称为 Stimuli-SoS 的基于模型的方法，以支持创建用于 SoS 模拟的刺激生成器。Stimuli-SoS 使用软件架构描述来自动创建此类生成器。具体来说，这种方法将 SoSADL（一种 SoS 的正式架构描述语言）转换为用 DEVS（一种模拟形式主义）表达的动态模型。我们进行了一个案例研究，其中 Stimuli-SoS 用于自动生成用于模拟洪水监测 SoS 的刺激生成器。结果我们运行具有 69 个组成系统的 SoS 架构配置的模拟，即 42 个传感器、9 个众包系统和18架无人机。为每种类型的成分自动生成刺激生成器。这些刺激生成器能够接收来自数据库的输入数据并为成分生成预期的刺激，从而允许将成分系统的互操作模拟到洪水监测 SoS 中。使用 Stimuli-SoS，我们在 6 小时多一点的时间内模拟了 38 天的洪水监测。刺激生成器正确地将数据转发给模拟，该模拟能够在洪水事件期间重现由 SoS 触发的 29 次洪水警报。特别是，Stimuli-SoS 的生产率几乎是为相同类型的模拟生成数据的手动方法的 65 倍。结论我们的方法成功地自动推导了一个功能性刺激生成器，该生成器可以重现模拟 SoS 的环境条件。特别是，