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A Roadmap for Simulation-Based Testing of Autonomous Cyber-Physical Systems: Challenges and Future Direction

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arxiv 2405.01064 v1 pith:7CHNXZS7 submitted 2024-05-02 cs.SE

classification cs.SE
keywords systemsautonomoustestingacpsschallengessimulation-basedsoftwareautomation
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As the era of autonomous cyber-physical systems (ACPSs), such as unmanned aerial vehicles and self-driving cars, unfolds, the demand for robust testing methodologies is key to realizing the adoption of such systems in real-world scenarios. However, traditional software testing paradigms face unprecedented challenges in ensuring the safety and reliability of these systems. In response, this paper pioneers a strategic roadmap for simulation-based testing of ACPSs, specifically focusing on autonomous systems. Our paper discusses the relevant challenges and obstacles of ACPSs, focusing on test automation and quality assurance, hence advocating for tailored solutions to address the unique demands of autonomous systems. While providing concrete definitions of test cases within simulation environments, we also accentuate the need to create new benchmark assets and the development of automated tools tailored explicitly for autonomous systems in the software engineering community. This paper not only highlights the relevant, pressing issues the software engineering community should focus on (in terms of practices, expected automation, and paradigms), but it also outlines ways to tackle them. By outlining the various domains and challenges of simulation-based testing/development for ACPSs, we provide directions for future research efforts.

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Cited by 1 Pith paper

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  1. Using Cooperative Co-evolutionary Search to Generate Metamorphic Test Cases for Autonomous Driving Systems

    cs.SE 2024-12 conditional novelty 6.0 of 10

    CoCoMEGA combines metamorphic testing with cooperative co-evolutionary search and finds more severe, diverse autonomous-driving safety violations in simulation than random search and a standard genetic algorithm.

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