As technology advances at a rapid pace, modernizing legacy systems has become essential for companies seeking innovation and competitiveness. StackSpot AI addresses this need by offering a cutting-edge development assistant designed to surpass the limitations of traditional “lift and shift” software modernization methods.
To showcase StackSpot AI’s capabilities, we examine the COBOL to Java modernization process, which achieves an average success rate of 93%.
Want to see how StackSpot AI can be used in COBOL to Java modernization? Keep reading!
Reinventing the Modernization of Legacy Systems
Our goal extends beyond automating the transcription of COBOL code into Java; we aim to deliver an intelligent tool that helps developers understand, restructure, and rewrite legacy code into a microservices architecture while preserving the essence of the business.
The premise is clear: avoid creating “JaBOL,” a hybrid of outdated COBOL practices and Java, resulting in code that fails to fully leverage modern development capabilities. Instead, StackSpot AI acts as a catalyst for innovation, drastically reducing the time needed to understand legacy systems and accelerating the creation of clean, maintainable Java code that aligns with current best practices.
With StackSpot AI, developers gain valuable insights and actionable suggestions, enabling them to reshape the technological past and build a resilient, scalable digital future.
Discover how StackSpot optimizes your modernization process!
The Art of Prompt Engineering in Software Modernization
At StackSpot AI, we recognize that modernizing legacy systems is a complex undertaking that requires precision and deep knowledge of the technologies involved. We apply Prompt Engineering frameworks to guide StackSpot AI in transforming COBOL programs into modern and efficient Java solutions.
Prompt Strategies for Effective Modernization
We employ diverse prompt strategies to maximize the efficiency of the AI tool. To achieve seamless modernization from COBOL to Java, we recommend the following strategies:
- Prompt Preparation: Before initiating the process, we provide StackSpot AI with the essential context to grasp the essence of the modernization project.
- Chain of Thought: We break down complex problems into smaller, manageable steps, enabling StackSpot AI to tackle them systematically.
- Perspective: We guide StackSpot AI to consider multiple approaches to modernization challenges.
- Tabular: For structured data, we craft prompts that enhance StackSpot AI’s ability to comprehend and manipulate the data.
General Purpose Prompts
Mastering general-purpose prompt templates is crucial, as they can significantly improve the effectiveness of your prompts and the AI’s corresponding responses.
RGC (Role, Goal, Context): We clearly define StackSpot AI’s role, the objective to be achieved, and the project context, including any constraints.
I Want You to Act Like: We instruct StackSpot AI to assume a specific role, such as an expert programmer, to complete the assigned task.
Deploying COBOL to Java Modernization
Having explored how to maximize the benefits of Prompt Engineering, we can now apply this expertise with StackSpot AI to tackle one of today’s most complex technological challenges: modernizing COBOL to Java.
In this process, StackSpot AI acts as a developer proficient in both COBOL and Java, tasked with transforming a COBOL program into a microservices-based Java architecture. The AI is guided in rewriting the COBOL program into a Java application, addressing tasks such as:
- Defining input and output parameters;
- Designing request and response classes with data validation;
- Creating REST controllers with validation and exception handling, along with their corresponding unit tests;
- Implementing services and their unit tests for each feature;
- Preparing an Insomnia collection to test endpoints.
Want another example of legacy system modernization? Check out this tutorial on modernizing Android mobile systems with StackSpot AI.
Results
The effectiveness of artifacts generated by StackSpot AI is evaluated based on their utilization rate. A low utilization rate suggests a greater need for manual intervention by developers. For the modernization from COBOL to Java, the classes generated by StackSpot AI achieved an average utilization rate of 93%.
Lessons learned in the COBOL to Java modernization process
Contextualizing database tables and program queries proved to be an effective method of “prompt priming,” laying a solid foundation for subsequent prompts that adhered more closely to the directive to “Use meaningful names for various code elements.”
Breaking down work into smaller, sequential tasks yielded higher-quality results compared to prompts requesting extensive answers. For instance, focusing on one feature at a time, starting with the innermost routine and moving outward, proved more effective.
Utilizing the context of previous requests, particularly recent ones, to generate related responses has been highly beneficial. For example, after understanding and implementing the input (request) and output (response) classes, the next logical step is to design the controller class.
Selecting appropriate Knowledge Sources for the wizard is critical, particularly for explaining source code. Program explanations generated by the wizard can be formatted and saved as a Knowledge Source for future use. This practice enhances prompt effectiveness—making them more concise—and improves the accuracy of responses.
From Tradition to Innovation: StackSpot AI promotes modernization from COBOL to Java
StackSpot AI is a comprehensive AI-powered development platform built to modernize legacy systems and mainframes. With StackSpot, you can gain insights into your existing code, design a modern solution tailored to business needs, manage a coexistence phase, and ultimately migrate both the environment and data. Visit this page to discover how StackSpot AI streamlines your modernization journey.
This process becomes even more efficient with StackSpot AI Agents. This feature enables the creation and utilization of automated systems that employ AI to perform specific tasks and make decisions based on previously provided information. StackSpot AI Agents are highly customizable, designed to meet the unique needs of your project.
Conclusion
StackSpot AI significantly enhances software modernization by seamlessly converting COBOL programs into accurate Java microservice architectures. What once seemed nearly impossible is now attainable, thanks to the tool’s high accuracy.
Break free from legacy software that drives up costs and risks, disrupts your development team’s workflow, diminishes their Developer Experience, and stifles your company’s growth and progress.
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