What is AI Legacy Code Modernisation
AI Legacy Code Modernisation refers to the process of using artificial intelligence to update and improve outdated software code, particularly legacy systems written in languages like COBOL, into modern, maintainable formats such as Java. This technology not only converts the code but also ensures that the converted code is readable and functional, maintaining the original program's behavior while enhancing its usability and compatibility with modern systems.
Features of AI Legacy Code Modernisation
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Automatic Conversion: AI tools can automatically convert legacy code into modern languages like Java, saving significant time and effort.
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Safety and Validation: Converted code is rigorously tested using AI-powered test suites to ensure it behaves identically to the original COBOL programs.
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Readable Output: The resulting Java code is designed to be easily readable and maintainable, resembling code written by humans.
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Cost Efficiency: Modernised code utilizes open-source libraries and cloud primitives to reduce costs and enhance functionality.
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Continuous Delivery: The conversion process does not require a code freeze, allowing projects to continue progressing without interruption.
How to use AI Legacy Code Modernisation
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Identify the Need: Determine which parts of your legacy codebase need modernisation.
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Select an AI Tool: Choose an AI-powered tool designed for legacy code modernisation, such as those specifically trained for COBOL to Java conversion.
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Initiate Conversion: Start the conversion process, allowing the AI to analyze and transform the code.
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Review and Modify: After conversion, review the new code to ensure it meets your requirements and make any necessary adjustments.
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Integrate and Deploy: Integrate the modernised code into your existing systems and deploy it to production environments.
Pricing of AI Legacy Code Modernisation
The pricing for AI Legacy Code Modernisation services can vary widely depending on the size of the codebase, the complexity of the conversion, and the specific features required. Typically, pricing models include subscription-based services, pay-per-use, or project-based quotes. It's advisable to contact service providers directly for detailed pricing information tailored to your specific needs.
Useful tips for using AI Legacy Code Modernisation
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Backup Original Code: Always keep a backup of the original legacy code before starting the conversion process.
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Gradual Implementation: Consider modernising the codebase in phases to manage risks and ensure smooth integration.
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Continuous Monitoring: After conversion, continuously monitor the performance and behavior of the modernised code to catch any issues early.
Frequently asked questions about AI Legacy Code Modernisation
What languages can be modernised using AI?
AI tools are particularly effective with languages like COBOL, but they can also handle other legacy languages and convert them into modern languages such as Java or Python.
Is the converted code fully functional?
Yes, the converted code is designed to be fully functional, maintaining the original program's behavior while being readable and maintainable.
Can AI modernisation tools work offline?
Many AI modernisation tools are designed to operate offline, ensuring data privacy and security, especially when dealing with sensitive legacy code.
How does AI ensure the quality of the converted code?
AI tools use advanced testing and validation techniques, including AI-powered test suites, to ensure that the converted code behaves identically to the original and meets modern coding standards.