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How to accelerate DDD practice using Amazon Q Developer

Lv300

Lv300

8/24/2024 21:00 (UTC)
Session Info

DDD is important practice to develop complex modern application.

But that practice is difficult to understand and to use in your application especially beginner of application developing.

I will introduce how Amazon Q Developer help you for DDD practice and show some demos.

Masao Kanamori

Masao Kanamori

- AWS Employee -

Session Category
Developer tools
AWS Services
Amazon Q Developer
Session Materials
Session Archive
Session Summary (by Amazon Bedrock)
    The presentation discusses how to accelerate Domain-Driven Design (DDD) practices using Amazon's developer tools, particularly Amazon CodeWhisperer. Key points include: 1. DDD is a software design approach that reflects business domains in system architecture. 2. Strategic design focuses on finding domain models and building shared understanding among stakeholders. 3. Tactical design implements the domain model using specific practices and approaches. 4. Three main difficulties in applying DDD: a. Numerous practices to choose from b. Lack of guidance on integrating DDD with existing frameworks c. Limited access to experienced team members 5. Amazon CodeWhisperer can help overcome these challenges by: a. Generating UML diagrams (class and sequence) based on natural language prompts b. Creating source code and test cases that implement DDD practices c. Providing insights into existing project structures and frameworks 6. The presentation demonstrates how to use Amazon CodeWhisperer to: a. Generate class diagrams b. Create sequence diagrams c. Produce source code and test cases 7. A new feature, "@workspace," allows CodeWhisperer to use the entire project workspace as context for more accurate assistance. 8. The speaker emphasizes that while AI assistants like CodeWhisperer can be helpful, developers should still understand DDD principles and make their own judgments. 9. DDD may not be suitable for all applications, especially simple ones. The presentation concludes by highlighting the potential of AI-assisted development in implementing DDD practices while stressing the importance of human understanding and decision-making in the process.

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