Abstract:In the development of complex software systems, achieving semantic alignment between design and verification is crucial for ensuring system reliability and functional correctness. However, heterogeneity in modeling languages, semantics, and data structures across design and verification tools often leads to semantic inconsistencies during model transformation, insufficient toolchain interoperability, and inadequate verification coverage. To address these challenges, this paper proposes a layered transformation and multi-perspective cross-verification mechanism based on a Unified Intermediate Representation (UIR). Starting from the design model, Systems-Theoretic Process Analysis (STPA) is applied to conduct hazard analysis and identify unsafe control actions, from which safety constraints are extracted and cross-checked against existing functional, timing, and safety properties. Subsequently, a mapping from the design model to the UIR is constructed, and the structure, behavior, timing, and safety constraints are formally specified within a unified syntactic and semantic domain. On this basis, we define layered transformation rules, together with traceability metadata, that cover the above elements. From the UIR, complementary verification models, such as temporal, logical, and probabilistic models, are derived, and the safety constraints produced by STPA are systematically translated into verifiable properties. We then perform multi-perspective cross-verification, including source, intermediate, and target model consistency checking, temporal and logical property verification, probabilistic analysis, and satisfiability checking of safety constraints. Case studies on both an autonomous vehicle control system and a multi-domain collaborative Unmanned Aerial Vehicle (UAV) control system demonstrate that the proposed method improves verification coverage and accuracy, enhances traceability throughout transformation and verification, and provides a consistent and provable pathway for safety-driven development of complex systems.