Complete Agent-driven Model-based System Testing for Autonomous Systems

Kerstin I. Eder
(Department of Computer Science, University of Bristol, United Kingdom)
Wen-ling Huang
(Department of Mathematics & Computer Science, University of Bremen, Germany)
Jan Peleska
(Department of Mathematics & Computer Science, University of Bremen, Germany)

In this position paper, a novel approach to testing complex autonomous transportation systems (ATS) in the automotive, avionic, and railway domains is described. It is intended to mitigate some of the most critical problems regarding verification and validation (V&V) effort for ATS. V&V is known to become infeasible for complex ATS, when using conventional methods only. The approach advocated here uses complete testing methods on the module level, because these establish formal proofs for the logical correctness of the software. Having established logical correctness, system-level tests are performed in simulated cloud environments and on the target system. To give evidence that 'sufficiently many' system tests have been performed with the target system, a formally justified coverage criterion is introduced. To optimise the execution of very large system test suites, we advocate an online testing approach where multiple tests are executed in parallel, and test steps are identified on-the-fly. The coordination and optimisation of these executions is achieved by an agent-based approach. Each aspect of the testing approach advocated here is shown to either be consistent with existing standards for development and V&V of safety-critical transportation systems, or it is justified why it should become acceptable in future revisions of the applicable standards.

In Marie Farrell and Matt Luckcuck: Proceedings Third Workshop on Formal Methods for Autonomous Systems (FMAS 2021), Virtual, 21st-22nd of October 2021, Electronic Proceedings in Theoretical Computer Science 348, pp. 54–72.
Published: 21st October 2021.

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