Boost your coding output and accuracy with artificial intelligence tools coding with AI For Dummies introduces you to the many ways that artificial intelligence can make your life as a coder easier. Even if you’re br...
详细信息
ISBN:
(数字)9781394249145;9781394249152
ISBN:
(纸本)9781394249138
Boost your coding output and accuracy with artificial intelligence tools coding with AI For Dummies introduces you to the many ways that artificial intelligence can make your life as a coder easier. Even if you’re brand new to using AI, this book will show you around the new tools that can produce, examine, and fix code for you. With AI, you can automate processes like code documentation, debugging, updating, and optimization. The time saved thanks to AI lets you focus on the core development tasks that make you even more valuable. Learn the secrets behind coding assistant platforms and get step-by-step instructions on how to implement them to make coding a smoother process. Thanks to AI and this Dummies guide, you’ll be coding faster and better in no time.
Discover all the core coding tasks boosted by artificial intelligence
Meet the top AI coding assistance platforms currently on the market
Learn how to generate documentation with AI and use AI to keep your code up to date
Use predictive tools to help speed up the coding process and eliminate bugs
This is a great Dummies guide for new and experienced programmers alike. Get started with AI coding and expand your programming toolkit with coding with AI For Dummies.
Functional verification is based on the simulation of a circuit's hardware design language (HDL) model at register transfer level (RTL) and checking the results against the specification. Random stimuli generation...
详细信息
ISBN:
(纸本)9781424429554
Functional verification is based on the simulation of a circuit's hardware design language (HDL) model at register transfer level (RTL) and checking the results against the specification. Random stimuli generation has been largely used in different testbench architectures, but the manual coding of the stimuli sources may lead to the stimulation of redundant and invalid test vectors what causes a negative impact on verification performance. They can be eliminated by taking advantage of the dependencies of design's input parameters, splitting the simulation space into Parameter Domains. In this paper we propose an efficient functional verification methodology based on the Parameter Domains framework and constraint based random stimulation. Additionally, the paper presents a tool to automatically generate SystemC stimuli sources from module's parameter domains specification, providing an extra verification time save-up.
暂无评论