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GENERATIVE AI-POWERED ASSISTANT FOR DEVELOPERS [electronic resources] : accelerate software development with Amazon Q Developer
GENERATIVE AI-POWERED ASSISTANT FOR DEVELOPERS [electronic resources] : accelerate software development with Amazon Q Developer
상세정보
- 자료유형
- 전자책(국외)
- 미국국회도서관 청구기호
- QA76.76.A65
- 자관 청구기호
- 기본표목-개인명
- 표제와 책임표시사항
- GENERATIVE AI-POWERED ASSISTANT FOR DEVELOPERS [electronic resources] : accelerate software development with Amazon Q Developer / Behram Irani, Rahul Sonawane.
- 발행, 배포, 간사 사항
- 형태사항
- 1 online resource
- 내용주기
- 완전내용Cover -- Title Page -- Copyright and Credits -- Contributors -- Table of Contents -- Preface -- Part 1: Generative AI-Powered Assistant -- Chapter 1: Introduction to Generative AI-Powered Assistants -- What is generative AI? -- Common challenges faced by developers/builders -- Generative AI-powered assistants for developers/builders -- How developers/builders benefit from assistants -- Types of assistants for developers/builders -- Summary -- References -- Chapter 2: Introducing and Setting Up Amazon Q Developer -- Amazon Q nomenclature -- Amazon Q Developer basics
- 내용주기
- 완전내용Amazon Q Developer features -- Auto-code generation -- Code customizations -- Code transformations -- Code explanation, optimization, and update -- Code feature development -- Reference tracking -- Security scanning -- Integration with AWS services -- Amazon Q Developer tiers -- Amazon Q Developer free tier -- Amazon Q Developer Pro tier -- Amazon Q Developer setup for third-party IDEs -- VS Code -- JetBrains -- Visual Studio -- Amazon Q Developer setup for command line -- Amazon Q Developer setup for AWS coding environments -- Amazon SageMaker Studio -- Amazon EMR Studio -- JupyterLab
- 내용주기
- 완전내용AWS Glue Studio -- AWS Lambda -- Build on AWS with support from Amazon Q Developer -- Amazon Q permissions -- Conversational Q&A capability -- Troubleshoot AWS console errors -- Troubleshoot networking issues -- Optimal selection of Amazon EC2 instances -- Assist with AWS Support cases -- Assist during DevOps process in Amazon CodeCatalyst -- Summary -- References -- Part 2: Generate Code Recommendations -- Chapter 3: Understanding Auto-Code Generation Techniques -- What is a prompt? -- Single-line prompts for auto-code generation -- Multi-line prompts for auto-code generation
- 내용주기
- 완전내용Chain-of-thought prompts for auto-code generation -- Chat with code assistant for auto-code generation -- Common building methods of auto-code generation -- Single-line code completion -- Full function generation -- Block completion -- Line-by-line recommendations -- Cross-reference existing code -- Generating sample data -- Writing unit tests -- Explaining and documenting code -- Updating existing code -- Feature development -- Code transformation -- Summary -- References -- Chapter 4: Boost Coding Efficiency for Python and Java with Auto-code Generation
- 내용주기
- 완전내용An overview of the use case for weather data analysis -- Application requirements -- weather data analysis -- Prerequisites to access the OpenWeatherMap API -- Python auto-code generation using Amazon Q Developer for weather data analysis -- Solution blueprint for weather data analysis -- Use-case summary -- Java auto code generation using Amazon Q Developer for weather data analysis -- Solution blueprint for weather data analysis -- Use-case summary -- Summary -- References -- Chapter 5: Boost Coding Efficiency for C and C++ with Auto-Code Generation
- 요약 등 주기
- 요약Leverage Amazon Q Developer to boost productivity and maximize efficiency by accelerating software development life cycle tasks Key Features First book on the market to thoroughly explore all of Amazon Q Developer's features Gain an understanding of Amazon Q Developer's capabilities across the software development life cycle through real-world examples Build apps with Amazon Q Developer by auto-generating code in various languages within supported IDEs Purchase of the print or Kindle book includes a free PDF eBook Book Description Many developers face the challenge of managing repetitive tasks and maintaining productivity. This book will help you tackle both these challenges with Amazon Q Developer, a generative AI-powered assistant designed to optimize coding and streamline workflows. This book takes you through the setup and customization of Amazon Q Developer, demonstrating how to leverage its capabilities for auto-code generation, code explanation, and transformation across multiple IDEs and programming languages. You'll learn to use Amazon Q Developer to enhance coding experiences, generate accurate code references, and ensure security by scanning for vulnerabilities. The book also shows you how to use Amazon Q Developer for AWS-related tasks, including solution building, applying architecture best practices, and troubleshooting errors. Each chapter provides practical insights and step-by-step guidance to help you fully integrate this powerful tool into your development process. You'll get to grips with effortless code implementation, explanation, transformation, and documentation, helping you create applications faster and improve your development experience. By the end of this book, you'll have mastered Amazon Q Developer to accelerate your software development lifecycle, improve code quality, and build applications faster and more efficiently. What you will learn Understand the importance of generative AI-powered assistants in developers' daily work Enable Amazon Q Developer for IDEs and with AWS services to leverage code suggestions Customize Amazon Q Developer to align with organizational coding standards Utilize Amazon Q Developer for code explanation, transformation, and feature development Understand code references and scan for code security issues using Amazon Q Developer Accelerate building solutions and troubleshooting errors on AWS Who this book is for This book is for coders, software developers, application builders, data engineers, and technical resources using AWS services looking to leverage Amazon Q Developer's features to enhance productivity and accelerate business outcomes. Basic coding skills are needed to understand the concepts covered in this book.
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■5050 ▼aCover -- Title Page -- Copyright and Credits -- Contributors -- Table of Contents -- Preface -- Part 1: Generative AI-Powered Assistant -- Chapter 1: Introduction to Generative AI-Powered Assistants -- What is generative AI? -- Common challenges faced by developers/builders -- Generative AI-powered assistants for developers/builders -- How developers/builders benefit from assistants -- Types of assistants for developers/builders -- Summary -- References -- Chapter 2: Introducing and Setting Up Amazon Q Developer -- Amazon Q nomenclature -- Amazon Q Developer basics
■5058 ▼aAmazon Q Developer features -- Auto-code generation -- Code customizations -- Code transformations -- Code explanation, optimization, and update -- Code feature development -- Reference tracking -- Security scanning -- Integration with AWS services -- Amazon Q Developer tiers -- Amazon Q Developer free tier -- Amazon Q Developer Pro tier -- Amazon Q Developer setup for third-party IDEs -- VS Code -- JetBrains -- Visual Studio -- Amazon Q Developer setup for command line -- Amazon Q Developer setup for AWS coding environments -- Amazon SageMaker Studio -- Amazon EMR Studio -- JupyterLab
■5058 ▼aAWS Glue Studio -- AWS Lambda -- Build on AWS with support from Amazon Q Developer -- Amazon Q permissions -- Conversational Q&A capability -- Troubleshoot AWS console errors -- Troubleshoot networking issues -- Optimal selection of Amazon EC2 instances -- Assist with AWS Support cases -- Assist during DevOps process in Amazon CodeCatalyst -- Summary -- References -- Part 2: Generate Code Recommendations -- Chapter 3: Understanding Auto-Code Generation Techniques -- What is a prompt? -- Single-line prompts for auto-code generation -- Multi-line prompts for auto-code generation
■5058 ▼aChain-of-thought prompts for auto-code generation -- Chat with code assistant for auto-code generation -- Common building methods of auto-code generation -- Single-line code completion -- Full function generation -- Block completion -- Line-by-line recommendations -- Cross-reference existing code -- Generating sample data -- Writing unit tests -- Explaining and documenting code -- Updating existing code -- Feature development -- Code transformation -- Summary -- References -- Chapter 4: Boost Coding Efficiency for Python and Java with Auto-code Generation
■5058 ▼aAn overview of the use case for weather data analysis -- Application requirements -- weather data analysis -- Prerequisites to access the OpenWeatherMap API -- Python auto-code generation using Amazon Q Developer for weather data analysis -- Solution blueprint for weather data analysis -- Use-case summary -- Java auto code generation using Amazon Q Developer for weather data analysis -- Solution blueprint for weather data analysis -- Use-case summary -- Summary -- References -- Chapter 5: Boost Coding Efficiency for C and C++ with Auto-Code Generation
■520 ▼aLeverage Amazon Q Developer to boost productivity and maximize efficiency by accelerating software development life cycle tasks Key Features First book on the market to thoroughly explore all of Amazon Q Developer's features Gain an understanding of Amazon Q Developer's capabilities across the software development life cycle through real-world examples Build apps with Amazon Q Developer by auto-generating code in various languages within supported IDEs Purchase of the print or Kindle book includes a free PDF eBook Book Description Many developers face the challenge of managing repetitive tasks and maintaining productivity. This book will help you tackle both these challenges with Amazon Q Developer, a generative AI-powered assistant designed to optimize coding and streamline workflows. This book takes you through the setup and customization of Amazon Q Developer, demonstrating how to leverage its capabilities for auto-code generation, code explanation, and transformation across multiple IDEs and programming languages. You'll learn to use Amazon Q Developer to enhance coding experiences, generate accurate code references, and ensure security by scanning for vulnerabilities. The book also shows you how to use Amazon Q Developer for AWS-related tasks, including solution building, applying architecture best practices, and troubleshooting errors. Each chapter provides practical insights and step-by-step guidance to help you fully integrate this powerful tool into your development process. You'll get to grips with effortless code implementation, explanation, transformation, and documentation, helping you create applications faster and improve your development experience. By the end of this book, you'll have mastered Amazon Q Developer to accelerate your software development lifecycle, improve code quality, and build applications faster and more efficiently. What you will learn Understand the importance of generative AI-powered assistants in developers' daily work Enable Amazon Q Developer for IDEs and with AWS services to leverage code suggestions Customize Amazon Q Developer to align with organizational coding standards Utilize Amazon Q Developer for code explanation, transformation, and feature development Understand code references and scan for code security issues using Amazon Q Developer Accelerate building solutions and troubleshooting errors on AWS Who this book is for This book is for coders, software developers, application builders, data engineers, and technical resources using AWS services looking to leverage Amazon Q Developer's features to enhance productivity and accelerate business outcomes. Basic coding skills are needed to understand the concepts covered in this book.
■532 0▼3EBSCOhost▼a"EBSCO evaluates our products based on the Web Content Accessibility Guidelines (WCAG) and the related Section 508 and EN 301 549 regulations in the US and EU. Most EBSCO products are substantially conformant with WCAG 2.2 level AA." Source: https://connect.ebsco.com/s/article/EBSCO-VPATs?language=en_US. Last accessed April 22, 2025.
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