QA in verification

本博客探讨了在测试基准中决定将分数板数据输入直从生成器还是从物理接口获取的关键因素,以及两种方法的优缺点。同时解释了测试文件与环境文件约束的区别,并对比了声明式代码与顺序代码的特性及优势。
 

Q6: Which of the parts in the testbench should add data to the scoreboard?
A6: That’s a million dollar question…there are two main approaches and the decision between the two should be done according to the project you have at hand. The first approach, which is faster and simpler is to take scoreboard data straight from the generator. Its major drawback is that the scoreboard won’t function if you have to move from the block level to the system level. The second one is to take scoreboard data from the physical interface (sub question: what is lost if you get the data from the physical interface in the form of bits and bytes, instead of taking it from the generator? Hint: all the logical fields), and then reconstruct it. This will allow the scoreboard to work at system level as well.
Therefore the correct answer would be: it depends. If our DUT has a chance of becoming an internal block then go for the second option. If, on the other hand, it is not and data reconstruction is not trivial, go for the first one. You can read more about this subject here.


Q10: What is the difference between the constraints that are added through the test file, and those constraints that are placed in the environment files themselves?
A10: The constraints that are an integral part of the environment are those found in the specification document. They limit the generated data to the DUT’s “specified behavior”, i.e. to correct or erroneous data that the DUT should know how to handle according to the specification. The constraints in the test file, on the other hand, are intended to direct the test further (towards a specific potential bug in the design, or a coverage hole, for example) and are often not related at all to the specification.
It is important to remember that constraints placed inside the actual environment file should not limit the data any further then the specification does. Test constraints are meant to do just that.

Q11: Please explain the difference between declarative code (also known as static code), and sequential code, and give an example of each. What is the major advantage of controlling generation via declarative code? Which of the two is harder to debug?
A11: Simply put, sequential code is a piece of code that you can run step by step in a debugger. For example, a function is a block of sequential code. On the other hand, a lot of the code you write is declarative and can not be stepped through…common examples are function and variable declarations, or generation constraints in HVLs.
The major advantage of controlling generation via declarative code is that it makes the generation extendable. You can add further constraints (or cancel existing ones in SystemVerilog and with some effort in E as well), without modifications to the original code. For example, an external test file can be used to change the generated data. This advantage is the one that made all HVLs opt for this mode of writing.
The major disadvantage is that the code is that declarative code is a lot harder to debug, but that’s a small price to pay compared with the first advantage.

内容概要:本文围绕六自由度机械臂的人工神经网络(ANN)设计展开,重点研究了正向与逆向运动学求解、正向动力学控制以及基于拉格朗日-欧拉法推导逆向动力学方程,并通过Matlab代码实现相关算法。文章结合理论推导与仿真实践,利用人工神经网络对复杂的非线性关系进行建模与逼近,提升机械臂运动控制的精度与效率。同时涵盖了路径规划中的RRT算法与B样条优化方法,形成从运动学到动力学再到轨迹优化的完整技术链条。; 适合人群:具备一定机器人学、自动控制理论基础,熟悉Matlab编程,从事智能控制、机器人控制、运动学六自由度机械臂ANN人工神经网络设计:正向逆向运动学求解、正向动力学控制、拉格朗日-欧拉法推导逆向动力学方程(Matlab代码实现)建模等相关方向的研究生、科研人员及工程技术人员。; 使用场景及目标:①掌握机械臂正/逆运动学的数学建模与ANN求解方法;②理解拉格朗日-欧拉法在动力学建模中的应用;③实现基于神经网络的动力学补偿与高精度轨迹跟踪控制;④结合RRT与B样条完成平滑路径规划与优化。; 阅读建议:建议读者结合Matlab代码动手实践,先从运动学建模入手,逐步深入动力学分析与神经网络训练,注重理论推导与仿真实验的结合,以充分理解机械臂控制系统的设计流程与优化策略。
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