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Generative AI-Powered Assistant for Developers

You're reading from   Generative AI-Powered Assistant for Developers Accelerate software development with Amazon Q Developer

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781835089149
Length 416 pages
Edition 1st Edition
Tools
Concepts
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Authors (2):
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Behram Irani Behram Irani
Author Profile Icon Behram Irani
Behram Irani
Rahul Sonawane Rahul Sonawane
Author Profile Icon Rahul Sonawane
Rahul Sonawane
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Table of Contents (23) Chapters Close

Preface 1. Part 1:Generative AI-Powered Assistant FREE CHAPTER
2. Chapter 1: Introduction to Generative AI-Powered Assistants 3. Chapter 2: Introducing and Setting Up Amazon Q Developer 4. Part 2:Generate Code Recommendations
5. Chapter 3: Understanding Auto-Code Generation Techniques 6. Chapter 4: Boost Coding Efficiency for Python and Java with Auto-Code Generation 7. Chapter 5: Boost Coding Efficiency for C and C++ with Auto-Code Generation 8. Chapter 6: Boost Coding Efficiency for JavaScript and PHP with Auto-Code Generation 9. Chapter 7: Boost Coding Efficiency for SQL with Auto-Code Generation 10. Chapter 8: Boost Coding Efficiency for Command-Line and Shell Script with Auto-Code Generation 11. Chapter 9: Boost Coding Efficiency for JSON, YAML, and HCL with Auto-Code Generation 12. Part 3:Advanced Assistant Features
13. Chapter 10: Customizing Code Recommendations 14. Chapter 11: Understanding Code References 15. Chapter 12: Simplifying Code Explanation, Optimization, Transformation, and Feature Development 16. Chapter 13: Simplifying Scanning and Fixing Security Vulnerabilities in Code 17. Part 4:Accelerate Build on AWS
18. Chapter 14: Accelerate Data Engineering on AWS 19. Chapter 15: Accelerate Building Solutions on AWS 20. Chapter 16: Accelerate the DevOps Process on AWS 21. Index 22. Other Books You May Enjoy

Summary

In this chapter, we covered some of the challenges faced by developers during the DevOps process. We then introduced Amazon CodeCatalyst, a comprehensive software development service designed for development teams to rapidly construct, deploy, and scale applications on AWS.

After that, we leveraged a use case to demonstrate the different generative AI capabilities of the service. Amazon Q allows developers to rapidly add new features to software. Developers can create issues and assign them to Amazon Q for comprehensive understanding and recommendations for different approaches needed to solve the particular task provided as input. Q can also be prompted to provide revised approaches based on the comments that users provide. It then generates the code and creates a pull request so that reviewers can examine the proposed changes and either approve or request revisions before merging them back into the main repository.

We also explored how Amazon Q provides pull request...

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