片上网络（NoC）作为片上系统新的发展趋势，测试技术是影响其发展的重要因素。除需要有效的测试方法外，如何分配和调度有限的资源，规划测试尽快完成资源核测试是提高测试效率的关键。.本项目面向NoC技术，研究三维NoC测试策略，利用云进化算法快速稳定的寻优特点，应用于资源约束下的复杂三维NoC测试规划研究。采用重用NoC作为测试存取机制的技术实施并行测试；通过设计测试时序的概念对测试功耗、TSV数量、通道带宽等进行动态检测实现多重约束；结合三维NoC体系结构特点，基于虚通道、多播路由技术，提出带分复用实现多核测试数据共享一个物理TAM的策略设计二维云滴，建立多态云进化NoC测试规划模型，合理分配和调度有限资源；在云模型的进化中加入自然进化机制的交叉变异操作完成迭代寻优，实施传输和测试双重优化以最大化并行测试，缩短测试时间。并将多种策略有机结合，开展协同优化研究，进一步降低硬件开销，提高测试效率。

Network-On-Chip(NoC) is a new trend of development in system-on-chip, test technology of NoC is an important influencing factor besides test method in NoC development.But how to assign and plan the limit resources so as to do test schedule to finish the IP core test as fast as possible is becoming the key factor that decreases test cost..In order to solve the difficulty of NoC testing, this project designs test method for NoC and uses the cloud evolution algorithm which is fast and stable to study three-dimensional NoC(3D NoC) test scheduling. The project employs the NoC reuse as Test Access Mechanism(TAM) for parallel testing. It performs dynamic constraint of power consumption, TSV number and channel width by designing test timing sequence. By combining the structure characteristics of 3D NoC, the project proposes different data of cores by sharing the width of a TAM by bandwidth division multiplexing,Virtual Channel and multi-cast routing technology to design cloud droplets and builds multi-attitude cloud evolution NoC test scheduling model. The crossover and mutation of natural evolution mechanism are added into the evolution of cloud model to accomplish the iterative optimization. Its aim is to maximize the parallel testing while not increasing the cost of hard area. So we can shorten the testing time and improve the efficiency of testing. And combining of various strategies, the project will study further collaborative optimization, so as to accomplish higher test efficiency and decrease hardware cost.