Speaker: Marco di Biase
When: 12:30 - 13:30
Where: Social Data Lab, Building 28

A Critical Comparison of Issue- and Risk-based Approaches to Assess Technical Debt

In this lunch talk, we are going to present results from a recent study where we compared issue-based and risk-based measurements approaches to detect technical debt. We performed an empirical study on data gathered over 30,000 commits, both with risk- and issue-based technical debt, over 12 Apache Software Foundation projects. Further, we conducted a qualitative study on a subset of two of the projects to understand the benefits for the end-user when using both approaches together.