Reducing technical debt manually can be a time-consuming, never-ending process. Use tools to automate the process. Azul gives development teams an accurate and automated way to remove unused and dead code from their applications, which is a critical step to ensure application modernization success.
In this post you will learn:
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- Best practices that can help reduce technical debt
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- Systems and training can also be helpful
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- To really make an impact, use tools to automate technical debt reduction
Technical debt builds up when outdated, unused, or poorly written code persists in the codebase, slowing software development, increasing code maintenance and jeopardizing modernization efforts. Causes range from rushed planning and shifting requirements to obsolete technology and inconsistent coding practices.
In general, the larger and older a codebase, the more tech debt it contains due to the significant time and resources required to eliminate it. That means most application modernization initiatives will simply bring along the tech debt, slowing down and potentially jeopardizing the success of the project. And with all current versions of Java ending support in the same three-year window, tech debt will dramatically impact an enterprise’s ability to scale up their modernization initiatives.
Aren’t there any strategies for reducing technical debt?
Strategies for reducing technical debt range from manual best practices to automated tactics that can liberate people from drudge work. Here are a few strategies that some experts recommend.
| Best Practices for Reducing Technical Debt |
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| Educate the product owner on the true cost of technical debt: Keep story point values accurate for future stories that require resolving existing technical debt. Modularize your architecture: Take a firm stance on technical debt in new components or libraries in the application. Once agility is visible in these new components, teams will naturally want to extend those practices to other parts of the code. Write automated tests: Nothing prevents bugs better than automated tests and continuous integration. When a new bug is found, write a new test to reproduce it and fix the issue. If that bug ever resurfaces, the automated test will catch it before customers do. Atlassian, Say 'bye' to tech debt: Agile solutions for clean development |
| Organize Your Technical Debt to Manage It |
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| Categorize technical debt: Categorize your sources of technical debt based on its impact on performance, security, and maintainability. Rank the most critical issues to address first. Create a technical debt register: Keep a register of all identified technical debt to help you keep track of what’s been fixed and what still needs attention. Improve documentation: Good documentation is like a roadmap for your systems. It’s essential for understanding and tackling technical debt efficiently. Document existing systems and create comprehensive documentation for all systems, including hardware configurations and software setups. Elevate Technology, 8 Tips for Tackling Technical Debt at Your Company |
| Apply Management Strategies to Technical Debt |
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| Audit your AI-generated code: AI lets you crank out code rapidly, but people seem more adept at cranking out new code rather than fixing it. Too much of that mediocre code is being moved into production without review by expert developers or automated quality assurance checks. Apply governance to technical debt: A good governance program should set requirements for testing and QA as well as specify when humans should be involved instead of automated QA decisions, Buniva says. It should also address training requirements so that anyone developing code is educated on the standards. CIO, 6 Tips for Tackling Technical Debt |
Use tools to automate technical debt reduction
Azul, in conjunction with OpenRewrite, gives development teams an accurate and automated way to remove unused and dead code from their applications, which is a critical step to ensure application modernization success. As a result, enterprises can dramatically reduce the time, resources and costs associated with identifying and removing technical debt.
By combining Azul’s production-aware insights with OpenRewrite’s ability to safely and automatically transform code at scale, enterprises have a clear path to avoiding the looming “End of Support” crunch for their entire Java estate. It also provides a model for how runtime data and automated codebase updates can work together going forward to keep codebases lean, secure and ready for what’s next.
The quickest way to get started may be to engage with one of Azul’s partners that offer Java app modernization services. Partners are trained and certified by Azul, and can deliver strategic advice that can help minimize risk while project-managing your modernization projects at the kind of scale necessary to avoid the pending end of support crisis.
