Code Assistance For Application Modernization/Migration: A Comprehensive Comparison

Application modernization and migration are critical steps for organizations aiming to stay relevant and competitive in the ever-evolving tech landscape. To streamline these processes, developers often turn to AI-powered code assistance tools. In this blog, we'll delve into three prominent tools—GitHub Copilot, Google Duet AI, and AWS CodeWhisperer—analyzing their features, use cases, integration, security, and costs to help you make informed decisions.

GitHub Copilot:

Code Generation/Translation/Refactoring:

GitHub Copilot is a revolutionary AI pair programmer that excels in code generation, translation, and refactoring tasks. It supports multiple programming languages, making it versatile for a wide range of projects. By providing autocomplete-style suggestions based on open files or natural language comments, Copilot significantly accelerates coding workflows.

Code as Context:

Suggests code based on open files across IDE instances.

One notable feature is Copilot's ability to suggest code based on open files across Integrated Development Environment (IDE) instances. This fosters a seamless coding experience by maintaining context throughout the development process, ensuring that suggestions are more relevant and detailed.

Code Security Checks:

Detects general practices and security issues.

GitHub Copilot extends its utility beyond code generation, incorporating security checks. By detecting general programming practices and potential security vulnerabilities, it enhances code quality and ensures adherence to best practices.

Training Data Source:

Large training set from GitHub public repositories. [Link]

GitHub Copilot is trained on an extensive dataset extracted from public repositories on GitHub. As per the official documentation, "GitHub Copilot is powered by a generative AI model developed by GitHub, OpenAI, and Microsoft.

GitHub Copilot is trained on all languages that appear in public repositories. For each language, the quality of suggestions you receive may depend on the volume and diversity of training data for that language.". Its wide-ranging language support is a testament to the diversity of the training set, making it a valuable asset for developers working in various languages and frameworks.

Ease of Integration with IDE:

Flexible integration with popular IDEs.

Copilot is designed to integrate seamlessly with popular IDEs, including Visual Studio, Eclipse, Vim, Neovim, JetBrains, Azure Data Studio, and more. This broad compatibility ensures that developers can leverage its capabilities within their preferred development environment.

Data Security and IP Protection:

Encryption, access controls, auditing.

GitHub Copilot prioritizes data security and intellectual property protection[link]. It employs encryption, access controls, and auditing mechanisms to safeguard sensitive information and prevent unauthorized access.

Google Duet AI

Code Generation/Translation/Refactoring:

Google Duet AI provides several capabilities related to code generation, translation, and refactoring. It can generate code in various programming languages like Python, JavaScript, Prolog, Fortran, and Verilog using natural language descriptions. Duet AI can also provide real-time code suggestions, complete functions, and identify errors and vulnerabilities in the code. It can assist in code refactoring and migration to Google Cloud, making it faster and easier to update older software. [Link]

Code as Context:

Duet AI enhances its code generation capabilities by reading open files as context. This feature ensures that the suggested code is not only accurate but also aligned with the existing codebase. The information provided about Duet AI's "Code as Context" feature is comprehensive. Duet AI enhances its code generation capabilities by reading open files as context, ensuring that the suggested code is accurate and aligned with the existing codebase. This feature is particularly valuable as it minimizes the cognitive load on developers and streamlines the code generation process. [Link]

Code Security Checks:

In addition to code generation, The information provided about Duet AI's code security checks is comprehensive. Duet AI incorporates security checks, aligning with Google Cloud security compliances, and is designed with a focus on prioritizing safety and security, upholding the highest standards of data privacy and governance . It also provides "near-instant" analysis of security issues and potential attacks, reducing the legwork for security analysts and helping to prevent critical findings. Additionally, Duet AI's strict data governance policy ensures that users have control and ownership of their data and intellectual property, and the outputs of the models are covered by Google's IP indemnification policy. This comprehensive approach to security and compliance makes Duet AI a trustworthy and valuable tool for developers and security professionals within the Google Cloud ecosystem.[Link] [Link] [Link]

Training Data Source:

Duet AI is specifically trained on Google Cloud content, including documentation, sample code, and best practices. This focused training allows it to provide targeted and contextually relevant suggestions to users within the Google Cloud ecosystem. Additionally, Duet AI is designed to ensure that the code, inputs, and recommendations of users are not used for any product and model learning and development, and that their data and intellectual property remain exclusively theirs. The training data for Duet AI is sourced from Google Cloud data sources relevant to Google Cloud development [Link].

Ease of Integration with IDE:

Duet AI supports a wide array of Integrated Development Environments, including popular ones like Visual Studio Code, JetBrains IDEs, Cloud Workstations, and Cloud Shell Editor. Its compatibility with 20+ programming languages ensures that developers using diverse tech stacks can benefit from its features. Duet AI supports a wide array of Integrated Development Environments (IDEs), including popular ones like Visual Studio Code, JetBrains IDEs (IntelliJ, PyCharm, GoLand, WebStorm, and more), Cloud Workstations, and Cloud Shell Editor [Link].

Data Security and IP Protection:

Given that Duet AI is integrated into Google Workspace, it adheres to Google's stringent security and compliance standards. Users can trust that their data is handled securely, and that intellectual property is protected. Data not used for other customers: None of your content is used for model training outside of your domain without permission. Robust security and privacy commitments: Duet AI is designed to prioritize safety and security, upholding the highest standards of data privacy and governance. [Link]

AWS CodeWhisperer

Code Generation/Translation/Refactoring:

AWS CodeWhisperer is an AI-powered productivity tool that provides real-time, single-line or full-function code suggestions in your integrated development environment (IDE) and command line. It is designed to improve code quality, enhance development productivity, and assist developers in using AWS services more efficiently.

Code as Context:

Similar to the other tools, CodeWhisperer reads open files as context, allowing it to generate code that aligns with the existing codebase. However, its emphasis on AWS-focused development may limit its applicability in more general scenarios.

Code Security Checks:

CodeWhisperer incorporates security checks through a built-in code-scanning feature. It aligns with AWS compliances and actively scans for potential vulnerabilities, contributing to the overall security posture of the developed code.

AWS CodeWhisperer is designed to prioritize safety and security, upholding the highest standards of data privacy and governance[Link].

Training Data Source:

AWS CodeWhisperer is a generative AI service powered by a foundation model (FM) trained on various data, including Amazon and open source code. The model has been trained on vast amounts of publicly available code to improve its accuracy. Additionally, AWS CodeWhisperer understands comments written in natural language (in English) and can generate code suggestions based on this understanding. The training data for AWS CodeWhisperer includes billions of lines of Amazon and publicly available code, enabling it to provide real-time, customized code suggestions for developers[Link].

Ease of Integration with IDE:

AWS CodeWhisperer is designed to integrate seamlessly with various Integrated Development Environments (IDEs) and command lines, making it easy for developers to use. It can be integrated into various IDEs, including Visual Studio Code, IntelliJ, and AWS Cloud9, as well as on the AWS Lambda console. AWS CodeWhisperer also supports CLI completions and natural-language-to-bash translation in the command line. By providing integration with these IDEs and command lines, CodeWhisperer enables developers to access its powerful code review capabilities within their enhancing productivity and ease of use. Additionally, AWS CodeWhisperer provides a built-in reference tracker that detects whether a code suggestion might resemble publicly available code and can flag such suggestions.[Link]

Data Security and IP Protection:

Given its association with AWS, CodeWhisperer adheres to the high security and compliance standards set by Amazon. Users can trust the platform to handle their data securely and maintain robust intellectual property protection.

Pricing:

Practical Learning: Migrating an ASP.NET Classic Application to an Angular Application

In this practical learning experience, I compared GitHub Copilot, Google Duet AI, and AWS CodeWhisperer while migrating an ASP.NET Classic application to an Angular application. The migration process provided valuable insights into the strengths and limitations of each code assistance tool.

GitHub Copilot

GitHub Copilot provided focused suggestions at the file level but may not be ideal for entire projects or multiple instances. It is not explicitly designed for direct code translations; instead, a reverse and forward engineering approach might be more effective. Leveraging code as context, Copilot Chat by GitHub offered insights into complex concepts, aids in security vulnerability identification, and assists in error detection and resolution across code, terminal, and debugger.

Google Duet AI

Duet AI provided relevant and detailed suggestions based on file context, offering a promising productivity gain of around 33%. It is trained on Google Cloud content, ensuring accuracy in suggestions and compliance with Google Cloud security standards. Early experiences with newer features like indexing and debugging indicate potential for further productivity improvements.

AWS CodeWhisperer

CodeWhisperer suggested code at a high level, focusing on AWS-centric development. It performed security checks with AWS compliances, providing a secure coding environment. CodeWhisperer supported various languages and tools, making it versatile for a broad range of projects.

Conclusion

In conclusion, choosing the right code assistance tool depends on your specific project requirements, preferences, and the existing technology stack. Here's a concise summary of each tool:

• GitHub Copilot: Broad language support, flexible integration. Limited to file-level suggestions, not ideal for entire projects.
• Google Duet AI: Detailed suggestions based on file context, Google Cloud-trained. Early experience; additional features under evaluation.
• AWS CodeWhisperer: AWS focus, built-in code-scanning, wide language support. Limited to high-level suggestions.

Consider factors such as security, integration capabilities, and the nature of your project before making a decision. Each tool has its strengths, and the choice should align with your development goals and workflow preferences.