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If you’re involved in software development at any level, you’re likely familiar with generative AI code assistants. The AI code assistants are rapidly evolving and are now becoming an integral part of a developer’s daily workflows. With mainframes continuing to serve as the foundation for mission critical applications, modernizing mainframe applications is a top priority for many executives [1].
A common question though, how is watsonx Code Assistant for Z, IBM’s AI Code Assistant for mainframe application modernization, different from other coding assistants such as GitHub Copilot.
Let’s dive into details!
Deep analysis of application landscape
Unlike GitHub Copilot[2], IBM watsonx Code Assistant for Z helps discover and analyze enterprise applications through in-depth, interactive visual analysis. IBM watsonx code Assistant for Z provides analysis reports, including dynamic application flows, data layers, call routines and APIs.
Fine-tuned Generative AI for mainframe code
IBM wastonx Code Assistant for Z utilizes fine-tuned LLM models for mainframe use cases to generate natural language code explanations and transform COBOL to high-quality Java that is easier to maintain
Incremental and targeted modernization
Developers can visualize application dependencies to identify candidates for refactoring and leverage automation to slice code and create modular business services. In contrast, GitHub Copilot suggests manual rewrite of a function to refactor code [2].
Prioritized optimization recommendations
Transform applications with mainframe Quality-of-service
If you’re interested in knowing more about what watsonx Code Assistant for Z and how it can help accelerate mainframe application modernization, you can schedule a live demo and speak with one of our product specialists.
Explore watsonx Code Assistant for Z
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References
[1] https://www.ibm.com/thought-leadership/institute-business-value/report/mainframe-hybrid-cloud
[2] https://github.com/resources/whitepapers/modernizing-cobol-with-github-copilot
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