This paper presents an approach to calculating, visualizing, and communicating the costs of technical debt. Using these techniques, a technical leader can establish a baseline and set improvement goals that convert into measurably decreased business risk. As shown in this paper, by managing technical debt, a typical development organization can increase feature delivery efficiency by at least 25%
Technical debt is often mistaken for bad code in general. This is a dangerous fallacy that leads organizations to waste months on improvements that don’t have a clear business outcome or aren’t urgent.
Technical debt is not equal to code quality issues. Rather, technical debt is the excess cost resulting from code quality issues, not the time it takes to fix them. This means we need to look beyond traditional static code analysis techniques to identify technical debt.
Technical debt implies code quality issues. However, the opposite is not necessarily true. Just because some code lacks in quality, doesn’t mean it adds to technical debt. It might not even be an immediate problem.
An organization cannot act on all potential issues at once. It’s vital to prioritize the most critical code quality issues and address them first.
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