This article presents CREST, a novel domain-specific language for the modelling of cyber-physical systems. CREST is designed for the simple and clear modelling, simulation and verification of small-scale systems such as home and office automation, smart gardening systems and similar. The language is designed to model the flow of resources throughout the system. It features synchronous system evolution and reactive behaviour. CREST's formal semantics allow real-valued time advances and the modelling of timed system evolution. The continuous time concept permits the precise simulation of future system behaviour by automatically calculating next transition times. We present CREST in a practical manner, and elaborate on the Python-based DSL implementation and simulator.
Autonomous Driving Systems (ADSs) are promising, but must show they are secure and trustworthy before adoption. Simulation-based testing is a widely adopted approach, where the ADS is run in a simulated environment over specific scenarios. Coverage criteria specify what needs to be covered to consider the ADS sufficiently tested. However, existing criteria do not guarantee to exercise the different decisions that the ADS can make, which is essential to assess its correctness. ADSs usually compute their decisions using parameterised rule-based systems and cost functions, such as cost components or decision thresholds. In this paper, we argue that the parameters characterise the decision process, as their values affect the ADS’s final decisions. Therefore, we propose parameter coverage, a criterion requiring to cover the ADS’s parameters. A scenario covers a parameter if changing its value leads to different simulation results, meaning it is relevant for the driving decisions made in the scenario. Since ADS simulators are slightly uncertain, we employ statistical methods to assess multiple simulation runs for execution difference and coverage. Experiments using the Autonomoose ADS show that the criterion discriminates between different scenarios; and that the cost of computing coverage can be managed with suitable heuristics.
By bridging the semantic gap, domain-specific language (DSLs) serve an important role in the conquest to allow domain experts to model their systems themselves. In this publication we present a case study of the development of the Continuous REactive SysTems language (CREST), a DSL for hybrid systems modeling. The language focuses on the representation of continuous resource flows such as water, electricity, light or heat. Our methodology follows a very pragmatic approach, combining the syntactic and semantic principles of well-known modeling means such as hybrid automata, data-flow languages and architecture description languages into a coherent language. The borrowed aspects have been carefully combined and formalised in a well-defined operational semantics. The DSL provides two concrete syntaxes: CREST diagrams, a graphical language that is easily understandable and serves as a model basis, and , an internal DSL implementation that supports rapid prototyping—both are geared towards usability and clarity. We present the DSL’s semantics, which thoroughly connect the various language concerns into an executable formalism that enables sound simulation and formal verification in , and discuss the lessons learned throughout the project.
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