The technical debt metaphor is useful in capturing the long-term impacts of
tradeoffs taken during software maintenance between productivity (getting
something done sooner) and maintainability (degradation of the code's
quality over time). This webinar on Technical Debt will present
techniques and insights that help software engineers to identify and track
technical debt in their projects. We will outline how business and product
quality goals should affect the choice of approaches (and combinations of
approaches) for managing technical debt. More specifically, we will discuss
a set of automated approaches based on static code analysis that are likely
to spot problems in source code that have real impact on productivity and
defect proneness. Based on previous empirical studies, we will give further
advice on which types of debt can be found by these tools, and which types
are not yet detectable.
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