有效设计验证——基于Python与Cocotb的约束随机方法
Effective Design Verification -- Constrained Random with Python and Cocotb
AI总结：
本文评估基于Python与Cocotb的硬件验证方案的有效性，依托开源库实现约束随机化与覆盖率功能，对比其与行业标准SystemVerilog的功能及性能，验证其降低验证搭建成本的潜力。
摘要：
Python因语法简洁且3.7版本仅含35个关键字，成为全球应用最广泛的编程语言，同时受到硬件与软件工程师的青睐。基于Python的验证环境依托cocotb（协同测试平台）、cocotb-coverage等开源库，可实现测试平台与任意可用仿真器的对接，分别支持约束随机化与覆盖率统计功能。这些库能大幅简化测试平台开发流程，有望降低验证搭建成本。本文旨在评估搭载设计IP的Python-Cocotb验证方案的有效性，并将其功能特性与性能指标同当前硬件验证领域的事实标准语言SystemVerilog进行对比。
英文摘要：
Being the most widely used language across the world due to its simplicity and with 35 keywords (v3.7), Python attracts both hardware and software engineers. Python-based verification environment leverages open-source libraries such as cocotb and cocotb-coverage that enables interfacing the tesbenches with any available simulator and facilitating constrained randomization, coverage respectively. These libraries significantly ease the development of testbenches and have the potential to reduce the setup cost. The goal of this paper is to assess the effectiveness of a Python-Cocotb verification setup with design IPs and compare its features and performance metrics with the current de-facto hardware verification language i.e., SystemVerilog.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
