Modernization Readiness from 0 to 60 with Code Analysis and Prioritization
Applications and services are increasingly more disruptive. Customer needs and expectations are rising to meet these changes. To compete in these changing marketplaces, more traditional companies need to adapt. They need to become more agile, flexible, efficient, and scalable.
Modernizing business-critical legacy systems to meet rising customer demands is essential for any organization that wants to be competitive. It’s also the critical building block for digital transformation.
This article discusses how analyzing, plotting, and prioritizing legacy code can more quickly get your legacy systems ready for modernization.
Measuring Code Complexity and Technical Debt
The first step to modernizing a legacy application is to get a clear picture of your application. You can’t take off running if you’re hauling years worth of technical debt.
What is technical debt? Technical debt is the build up of development costs of additional work needed because a developer chose an easy solution instead of using a better or best practices development approach at the start. This technical debt accrues over the years—there’s no doubt that it lurks within your legacy applications.
Understanding the complexity of your code will help a digital transformation succeed; it will be easier to develop new digital services on a clean IT surface than trying to deal with the bulk of your legacy code all at once.
The quickest way to get a clear picture of your code is to perform a legacy code analysis. The right tool will provide visualizations for:
Database tables, relationships, and triggers
User interaction and usage
An effective legacy code analysis tool will look for dead or unused code code, focusing on clusters of functionality. This allows application re-engineering to happen naturally; developers can easily see where code can be consolidated with low effort and high return.
Removing unused functionality can save up to 20% of a modernization effort.
The use case data will reveal what the unused code analysis could not: it shows the features no one uses, and the ones everyone uses. This is a goldmine of data. Prioritization, change adoption, process efficiency, cost savings and performance improvement can all be derived from this information.
With both the code analysis and use case analysis complete, you’ll have a complete picture of the application and the effort it takes to modernize the valuable pieces.
With a clear picture of your code, dependencies, and functionalities, now you can begin plotting on a prioritization matrix.
So what is a code prioritization matrix? In short, it’s a simple graph that helps sort applications or business processes by order of value and importance. In this case, this prioritization matrix shows where business value relates to the effort of modernizing those applications or processes.