Year: 2024
Type: article
Abstract: The design and analysis of systems that combine computational behaviour with physical processes' continuous dynamics -such as movement, velocity, and voltage -is a famous, challenging task.Several theoretical results from programming theory emerged in the last decades to tackle the issue; some of which are the basis of a proof-of-concept tool, called Lince, that aids in the analysis of such systems, by presenting simulations of their respective behaviours.However being a proof-of-concept, the tool is quite limited with respect to usability, and when attempting to apply it to a set of common, concrete problems, involving autonomous driving and others, it either simply cannot simulate them or fails to provide a satisfactory user-experience.The current work complements the aforementioned theoretical approaches with a more practical perspective, by improving Lince along several dimensions: to name a few, richer syntactic constructs, more operations, more informative plotting systems and errors messages, and a better performance overall.We illustrate our improvements via a variety of examples that involve both autonomous driving and electrical systems.
DOI: 10.4204/eptcs.411.2
Authors: Pedro Mendes, Ricardo Correia, Renato Neves, José Proença
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4404541824