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technical debt

A tool for detecting Self-Admitted Security Debt (SASD) in software projects using NLP. Developed as part of my MEng dissertation at Queen's University Belfast.

We apply data science on the Technical Debt Dataset to uncover anti-patterns in the development of several open-source projects, while also providing guidelines that help reduce this debt. Code is open-source and transferrable to other projects.

DebtHunter helps developers to manage Self-Admitted Technical Debt (SATD) more effectively. DebtHunter can not only mine source code comments in Java projects but also associated issue trackers, to capture debt at an architecture level.