Intelligent optical computing chips have emerged as a promising solution for next-generation artificial intelligence hardware due to their high-speed broadband parallel processing capabilities, low energy-consumption, and low-latency computational characteristics. However, these chips face challenges including accumulated phase errors in complex optical paths and manufacturing process variations, necessitating high-precision, wide-bandwidth characterization and calibration technologies to achieve accurate control and practical implementation. Capitalizing on the performance advantages of photonic devices, optical vector analysis (OVA) techniques enable high-accuracy measurement, ultra-broadband characterization, and multi-dimensional analys of intelligent optical computing chips, thus serving as a crucial enabler for their applications. This paper systematically reviews the system architectures and operational principles of existing OVA technical approaches. By examining the design features and functional requirements of intelligent optical computing chips, we provide an in-depth analysis of the strengths and limitations of different technical routes. Furthermore, we discuss future development directions for OVA techniques and their application prospects in photonic device characterization and optical chip calibration.