Ai-Assisted Programming: Better Planning, Coding, Testing, and Deployment (Paperback)

Taulli, Tom

  • 出版商: O'Reilly
  • 出版日期: 2024-05-21
  • 定價: $2,400
  • 售價: 9.5$2,280
  • 語言: 英文
  • 頁數: 222
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1098164563
  • ISBN-13: 9781098164560
  • 立即出貨 (庫存 < 3)

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商品描述

Get practical advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, and design; coding; and debugging, testing, and documentation. With this practical book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs (ChatGPT, Bard, and Claude) to code-specific systems (GitHub Copilot, Tabnine, Cursor, and Amazon CodeWhisperer).

You'll also learn about more specialized generative AI tools for tasks such as text-to-image creation.

Author Tom Taulli provides a methodology for modular programming that aligns effectively with the way prompts create AI-generated code. This guide also describes the best ways of using general purpose LLMs to learn a programming language, explain code, or convert code from one language to another.

This book examines:

  • The core capabilities of AI-based development tools
  • Pros, cons, and use cases of popular systems such as GitHub Copilot and Amazon CodeWhisperer
  • Ways to use ChatGPT, Bard, Claude, and other generic LLMs for coding
  • Using AI development tools for the software development lifecycle, including requirements, planning, coding, debugging, and testing
  • Prompt engineering for development
  • Using AI-assisted programming for tedious tasks like creating regular expressions making chron jobs and GitHub Actions
  • How to use AI-based low-code and no-code tools

商品描述(中文翻譯)

在這本實用書中,您將獲得有關如何運用人工智慧開發工具於程式碼創建的各個階段(包括需求、規劃、設計、編碼、除錯、測試和文件撰寫)的實用建議。無論是初學者還是有經驗的開發人員,都將學習如何使用各種工具,從通用的語言模型(如ChatGPT、Bard和Claude)到針對程式碼的特定系統(如GitHub Copilot、Tabnine、Cursor和Amazon CodeWhisperer)。

您還將了解更專門的生成式人工智慧工具,用於文本到圖像的創建等任務。

作者Tom Taulli提供了一種模塊化編程的方法論,與提示如何創建AI生成的程式碼的方式相互配合。本指南還描述了使用通用語言模型學習編程語言、解釋程式碼或將程式碼從一種語言轉換為另一種語言的最佳方法。

本書探討了以下內容:
- 基於人工智慧的開發工具的核心能力
- 流行系統(如GitHub Copilot和Amazon CodeWhisperer)的優缺點和使用案例
- 使用ChatGPT、Bard、Claude和其他通用語言模型進行編碼的方法
- 在軟體開發生命週期中使用人工智慧開發工具,包括需求、規劃、編碼、除錯和測試
- 開發中的提示工程
- 使用人工智慧輔助編程處理繁瑣任務,如創建正則表達式、製作定時任務和GitHub Actions
- 如何使用基於人工智慧的低代碼和無代碼工具