Comparative Analysis of Functional Verification Strategies for RISC-V with Potential Use in CV-QKD Systems

Abstract

With the advancement of quantum computing, traditional cryptographic algorithms have become vulnerable, demanding solutions based on physical principles, such as continuous-variable quantum key distribution (CV-QKD). One of the main challenges for the practical adoption of CV-QKD lies in the digital signal processing (DSP) and post-processing stage, which imposes strict requirements for performance, reliability, and robustness against noise and faults. In this context, architectures based on the open fifth-generation Reduced Instruction Set Computing (RISC-V) standard have proven promising for building application-specific instruction set processor (ASIP) and specialized system-on-chip (SoCs), due to their flexibility, customization capabilities, and growing support ecosystem. However, ensuring the functional reliability of such systems requires the application of rigorous verification processes. This paper presents a comparative study of four complementary functional verification approaches: modular block-based verification, instruction-level transaction-based verification, black-box verification, and cycle-by-cycle comparison. Each approach was evaluated in terms of coverage, implementation complexity, and fault visibility. The study also highlights how these methods complement each other when applied in layered verification environments. The results show that no single approach can efficiently meet all requirements. High-level strategies are better suited for integration testing and broad functional validation, while low-level techniques are essential for localized debugging and precise timing analysis. This reinforces that verification success relies more on strategic integration than on a single optimal method. The findings indicate that adopting hybrid, layered solutions provides better scalability, supports regression testing, and improves both coverage and alignment with the security and performance goals required by CV-QKD systems.