This presentation was part of the Seventh International Workshop on Managing Technical Debt, held in conjunction with the 31th International Conference on Software Maintenance and Evolution (ICSME 2015).
In classic economics, when borrowing an amount of money that causes a debt to the issuer, it is not usual to have interest that can become larger than the principal. In the context of technical debt, however, accumulated debt in the form of interest can in some cases quickly sum up to an amount that at some point becomes larger than the effort required to repay the initial amount of technical debt. In this presentation we propose an approach for estimating this breaking point. Anticipating how late the breaking point is expected to come can support decision making with respect to investments on improving quality. The approach uses a search-based optimization tool that is capable of identifying the distance of an actual object-oriented design to the corresponding optimum one.