JTA provides an architectural basis for modeling, designing, and assessing scenario-based validation in safety-critical software and shows that link-loss scenarios are comparatively mature, whereas state-estimation anomaly scenarios remain harder to validate because evidence alignment and attribution semantics are weaker.
Abstract
Validation adequacy in safety-critical software depends on more than the system under test. Critical scenarios must be constructed under controlled conditions, execution evidence must be aligned into verdict-ready form, and abnormal outcomes must be attributable to actionable causes. Existing testability research remains largely artifact-centric and offers little architectural support for reasoning about the combined capability of the scenario, the test system, and the system under test. Joint Testability Architecture (JTA) addresses this gap by treating those three elements as a single object of analysis and design. It characterizes validation capability along three dimensions--controllability, observability, and isolability--and organizes them through three domains, three bridges, and an analysis-design-evaluation-refinement loop. JTA also introduces scenario contracts, joint capability assessment, validation blind-spot identification, and bridge-oriented design actions that map capability gaps to concrete improvements in control points, evidence organization, and attribution boundaries. An illustrative analysis of ArduPilot failsafe validation shows that link-loss scenarios are comparatively mature, whereas state-estimation anomaly scenarios remain harder to validate because evidence alignment and attribution semantics are weaker. JTA is not a replacement for existing testing or safety-analysis techniques; it provides an architectural basis for modeling, designing, and assessing scenario-based validation in safety-critical software.
: This paper presents an automated approach to deriving informal test cases from Requirements Interchange Format (ReqIF)-structured system requirements based on general-purpose Large Language Models (LLMs) with integrated linkage to test evidences based on Digital Dependability Identities (DDIs). Our method enables scenario-based testing while drastically reducing effort and cost: test cases become available within hours instead of months. The automation supports formal traceability, safety argumentation, and change impact analysis. An automated conversion of derived test cases into ASAM OpenScenario (XOSC) and Open Test Sequence Exchange (OTX) formats accelerates design and implementation of platform-independent, executable test specifications while improving their reuse across development stages. A systematic review process allows domain experts to refine and extend generated specifications. We discuss testbed configuration including resource allocation, toolchain integration, and parameter initialization to satisfy test constraints and strengthen confidence in results against the original acceptance criteria. Finally, we execute the reviewed test cases in a simulated environment within a Virtual Continuous Testing (VCT) pipeline for efficient verification and validation in an X-in-the-Loop (XiL) testbed based on VCIP/FERAL. The closed-loop approach advances automated testing by combining efficiency, consistency, and scalability in test generation, which is showcased within an automotive use case.
Adam Bachorek, Stefan Schwenk, Naveed Akram et al.· International Conference on...· 0 citations
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