# On the Relationship between Self-Admitted Technical Debt Removals and Technical Debt Measures
## 6 Conclusions  
In this study, the relationship between SATD removal and TD values measured has been investigated using objective criteria. By leveraging a dataset of SATD and their removals in four open-source projects and by using the SonarQube tool for measuring the TD values, the trends of TD values when SATD removals occur have been analyzed. Overall, the results of the study indicate that SATD removals in few cases correspond to an effective reduction of TD values, while in numerous cases, the classes are indicated as SATD removals disappear from the repository. In particular, from the obtained results, it clearly emerges that in about half of the cases, the files are removed when SATD removals occur for all the four systems analyzed. Indeed, SATD removals correspond to class removal operations in 59.44% of cases and method removal in 19.49% of cases. Intuitively, this may indicate that developers tend to face technical debt resolution problems by eliminating the classes involved. This is a strong solution from a software design point of view and suggests that it is possible to hypothesize that the methods and functions belonging to the removed classes can be moved and integrated into other classes. The Method Changed corresponds to 17.68% of cases and Method Unchanged represents the remaining 3.39%. Regarding the delta of the technical debt between commit removals and the following commits, in 20.59% of cases, there is a negative value, while it increases or remains unchanged respectively for 12.61% and 13.35% of the cases. These results indicate that self-admitted technical debt by developers and its removal are too subjective, and this can lead to very different results from measurements made by means of objective tools. In the cases where commit removals correspond to a positive decrease of the technical debt, it is possible to note that in 84.04% of cases, the next commit preserves the improvement, exhibiting the same value of TD or the lower one. Then, developers tend to adopt strategies and carry out activities aimed at preserving the results obtained through a specific commit removal. This can be observed in the bar charts relating to the difference in the value of the Technical Debt between commits removal and its subsequent commit. In the graph, the highest percentage, excluding cases of class removals, corresponds to the preservation of the TD value. The study also considered the relationship with the OO metrics measured with the CK tool. In 12.54% of cases, it emerged that an improvement in the measure of the technical debt corresponds to an improvement of the part of metrics taken into consideration. In 6.03% of cases, the results are not aligned, and the improvement in the value of the TD corresponds to the worsening of most of the metrics considered. Finally, in the 7.67% of the cases, the not improved TD value has a positive effect, improving most of the metrics considered. However, in 13.60% of cases, it can be observed that the worsening of the TD also corresponds to the worsening of many of the metrics considered. Overall, the results indicate that self-admitted technical debt is not adequately used by the software developer. Indeed, their removals actually do not have a significant effect on the quality of the metrics' values. The results obtained will be used to address future research studies to improve the analysis about the technical debt objective and subjective measures. In the future, we envision to carry out a quantitative and qualitative investigation on the effects on quality profiles of software project deriving from the use of subjective measure of technical debt. Of course, in future work, more software projects will be considered with different characteristics, such as different programming languages and application domains. Moreover, the relationships with quality attributes will be extended to perform an in-depth quantitative and qualitative analysis. Conceptualization, L.A., M.I. ; Methodology, L.A., M.I. ; Formal Analysis Investigation M.C., A.D.V., L.N.