Freitag, 19. Mai 2023, 13:00 Uhr

Systematic Derivation of Feature-driven and Risk-based Test Strategies for Automotive Applications

  • Christopher Kugler, M.Sc. - Ehem. Lehrstuhl Informatik 11
  • Ort: Seminarraum 2202, Hauptbau, Ahornstr. 55



The automotive industry is currently characterized by a disruptive change in terms of electro-mobility and highly autonomous driving. Similarly, new mobility concepts pose particular challenges for quality assurance measures in automotive product development. Traditional, experience-based approaches for deriving quality assurance strategies do not address these challenges and lead to potentially high failure rates during product operation. Therefore, a risk-based approach for the derivation of feature-specific test strategies is proposed in this thesis, which enables the objective definition of test end criteria and, through appropriate prioritization, an increase in the efficiency and effectiveness of performed verification and validation activities. On the basis of a two-stage risk assessment, quality assurance measures can initially be defined in early project phases and then be refined for individual product features as soon as required information is available. A framework for the derivation of test strategies is presented, which considers the current state of the art with regard to functional safety and distinguishes the applied acceptance thresholds for test-end criteria based on previously defined risk classes. The presented approach is evaluated in context of series development projects, where the significance of the risk assessment is verified through data analysis. The test strategy applied in those projects is retrospectively evaluated and compared against the risk-based approach presented in this thesis in terms of achieved effectiveness and efficiency. Finally, two different concepts for measuring quality of automotive products are introduced and profound product release criteria are defined.

Es laden ein: die Dozentinnen und Dozenten der Informatik