Automatically Identifying Relations Between Self-Admitted Technical Debt Across Different Sources
This work addresses the lack of automated tools for SATD relation identification, which is important for software developers and maintainers to improve technical debt management, though it appears incremental as it builds on prior research on SATD relations.
The paper tackled the problem of automatically detecting relations between self-admitted technical debt (SATD) items across different sources like code comments and commit messages, achieving an average F1-score of 0.829, which outperforms baseline approaches by a large margin.
Self-Admitted Technical Debt or SATD can be found in various sources, such as source code comments, commit messages, issue tracking systems, and pull requests. Previous research has established the existence of relations between SATD items in different sources; such relations can be useful for investigating and improving SATD management. However, there is currently a lack of approaches for automatically detecting these SATD relations. To address this, we proposed and evaluated approaches for automatically identifying SATD relations across different sources. Our findings show that our approach outperforms baseline approaches by a large margin, achieving an average F1-score of 0.829 in identifying relations between SATD items. Moreover, we explored the characteristics of SATD relations in 103 open-source projects and describe nine major cases in which related SATD is documented in a second source, and give a quantitative overview of 26 kinds of relations.