Coding with AI for dummies
Book - 2024
"'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."--Provided by publisher.
Saved in:
- Subjects
- Published
-
Hoboken, NJ :
John Wiley & Sons, Inc
[2024]
- Language
- English
- Main Author
- Item Description
- Title proper from title page verso.
- Physical Description
- x, 324 pages : illustrations ; 24 cm
- Bibliography
- Includes index (pages 311-324).
- ISBN
- 9781394249138
- Introduction
- About This Book
- Foolish Assumptions
- Icons Used in This Book
- Beyond the Book
- Where to Go from Here
- Part 1. Techniques and Technologies
- Chapter 1. How Coding Benefits from AI
- Banishing Boring Tasks
- Spotting boring tasks
- Letting AI write the template
- Crafting CRUD with AI
- Helping with Syntax
- Stop remembering trivial details
- Hinting at code mastery
- Adapting to new syntax
- Linting with AI
- Detecting bad code with static code analysis
- Integrating AI with static code analysis
- Using AI as a Tutor
- Studying AI's potential in education
- Avoiding potential pitfalls
- Pairing Up with AI
- Overview of pair programming styles
- Understanding the pros and cons of pair programming with AI
- AI pair programming session
- Chapter 2. Parsing Machine Learning and Deep Learning
- Decoding Machine and Deep Learning
- Defining key concepts
- Thinking about neural networks
- Training and testing models
- Demystifying Natural-Language Processing
- History of NLP
- Overcoming the challenges of NLP
- Understanding Transformers
- Learning to pay attention
- Getting tokens
- Illuminating Generative AI Models
- Recognizing AI's Limitations
- Language models are bad at math
- Language models are wordy
- AI has limited knowledge
- AI lacks common sense
- AI has accuracy issues
- AI has the potential to be biased
- Chapter 3. AI Coding Tools
- Navigating GitHub Copilot
- Installing the Copilot plug-in
- Working efficiently with Copilot
- Using keyboard shortcuts
- Exploring Tabnine
- Installing Tabnine
- Setting up Tabnine
- Understanding Tabnine's AI-driven code completion
- Reviewing Replit
- Starting a website with Replit
- Exploring the Replit workspace
- Pairing up with Replit AI
- Chapter 4. Coding with Chatbots
- Improving Your Prompts
- Adjusting the temperature
- Deciphering the elements of a prompt
- Open-ended versus closed-ended prompts
- Using different types of prompts
- Prompting like a pro
- Chatting with Copilot
- Understanding slash commands
- Knowing Copilot's agents
- Getting the most out of Copilot Chat
- Chatting with ChatGPT
- Signing up and setting up
- Setting custom instructions
- Diving into the OpenAI Platform
- Checking your credits
- Messing around in the playground
- Running examples
- Playing the roles
- Adjusting the model's settings
- Getting an API key
- Developing a Chatbot with OpenAI
- Part 2. Using AI to write Code
- Chapter 5. Progressing from Plan to Prototype
- Understanding Project Requirements
- Determining the software requirements
- Domain requirements
- Functional requirements
- Non-functional requirements
- Writing an SRS
- Generating Code from an SRS
- Using a zero-shot approach
- Breaking down the problem
- Blending Manually Written and AI-Generated Code
- Writing the prompt
- Writing the server
- Submitting follow-up prompts
- Testing the server
- Implementing few-shot prompting on the server
- Improving the client
- Moving logic from AI to the client
- Tips and Tricks for Code Generation
- Don't stop coding
- Be specific
- Think in steps
- Ask follow-up questions
- Check the official documentation
- Use examples and context
- Prioritize security
- Keep learning
- Keep your tools updated
- Be mindful of AI's limitations
- Chapter 6. Formatting and Improving Your Code
- Using AI Tools for Code Formatting
- Setting up your formatting tools
- Using Prettier to automate code formatting
- Refactoring with AI
- Recognizing code smells
- Detecting code smells with Copilot
- Refactoring safely
- Generating Refactoring Suggestions
- Setting event listeners correctly
- Removing the magic number
- Reducing global data
- Fixing long functions
- Fixing inconsistent naming
- Lack of comments
- Making AI play tic-tac-toe better
- Chapter 7. Finding and Eliminating Bugs
- Knowing Your Bugs
- Strategies for detecting bugs
- Identifying common types of bugs
- AI-assisted bug reporting with Jam
- Preventing Bugs with Linting
- Installing a linter
- Installing the ESLint extension
- Fixing your code with a linter
- Combining linting with AI
- Changing the rules
- Detecting Bugs with AI
- Automating Bug Fixes with AI
- Introducing Snyk
- Executing automated bug fixes
- Verifying automated bug fixes
- Knowing when to automate
- Chapter 8. Translating and Optimizing Code
- Translating Code to Other Languages
- Preparing your code for translation
- Exploring translation strategies
- Translating a complete program using GPT-4
- Verifying translated code
- Optimizing Your Code with AI
- Getting code optimization suggestions
- Avoiding premature optimization
- Part 3. Testing, Documenting, and Maintaining Your Code
- Chapter 9. Testing Your Code
- Writing a Test Plan
- Deciding between formal and agile
- Stepping through the test planning process
- Understanding the role of AI in test planning
- Identifying core functionalities
- Generating test scenarios
- Working with a Testing Framework
- Installing Jest
- Running Jest
- Generating test cases
- Reading a coverage report
- Analyzing test results
- Test-Driven Development with AI
- Chapter 10. Documenting Your Code
- Working with Documentation Bots
- Building your own documentation bot
- Testing your documentation assistant
- Generating Code Comments and Annotations
- Installing and testing Mintlify Doc Writer
- Commenting on Underscore
- Creating Visual Documentation
- Generating a sequence diagram
- Generating a requirements diagram
- Automating API Documentation with AI
- Documenting a REST API
- Creating an API documentation chatbot
- Chapter 11. Maintaining Your Code
- Knowing the Four Types of Maintenance
- Corrective software maintenance
- Adaptive software maintenance
- Perfective software maintenance
- Preventative software maintenance
- Utilizing AI for Code Maintenance
- Enhancing Code Quality with AI
- Understanding technical debt
- Getting started with Code Climate
- Enabling the text coverage report
- Analyzing code quality metrics
- Making AI-assisted code quality improvements
- Part 4. The Part of Tens
- Chapter 12. Ten More Tools to Try
- Amazon CodeWhisperer
- Sourcegraph Cody
- DeepMind AlphaCode
- Google Bard
- Codeium
- Claude
- Microsoft IntelliCode
- Sourcery
- Bugasura
- UserWay
- Chapter 13. Ten AI Coding Resources
- Code.org's AI Resources
- Kaggle
- Google's Dataset Search
- edX
- Edabit
- StatQuest
- AI4All Open Learning
- Gymnasium
- Fast.ai
- Microsoft Learn
- Index