# On the Relationship between Self-Admitted Technical Debt Removals and Technical Debt Measures
## 4 Results
#### 4.1.1 Change in TD Value between Commit Removal and Previous Commit  
For each analyzed system, Table 3 shows, in the first column, the type of delta between the commit removal and the previous commit, and in the second column, the number of files analyzed. The change in the technical debt values, delta, is distinguished in 4 types of possible change observed: file not found, unchanged, increased, and decreased. In the case of Log4j, Table 3 shows that for 46.03% (29 files), the variation in the TD could not be assessed, as the analyzed file was absent in at least one of the commits to be analyzed. However, for 31.75% of cases (20 files), there was a decrease in the value of the TD between the previous commit and the commit removal considered, demonstrating that effectively, the changes performed by the software developers lead to a lower value of the technical debt objectively measured on the classes subject to the interventions. In particular, the effect of this reduction is not trivial; indeed, the intensity of change observed in the TD value compared to one of the previous commits ranges from 2 to 80%. However, in 6.35% of cases (4 files), no change in the analyzed value was found. Finally, for the remaining 15.87% of cases (10 files), the TD values increase. These results are not expected, as it means that the percentages indicate that the changes in the source code made to perform a SATD removal do not always lead to a more objective reduction of the TD. More specifically, in the commits analyzed, there was an intensity of increase in the TD value that ranges between 2% and 100%, with a particular case where the increase is even equal to 173% because the TD value goes from 15 to 41 min. In Gerrit, it can be observed that in 45.07% of cases (32 files), it was not possible to measure the variation of the TD due to the absence of the file with SATD in the commit. However, for 23.94% of the cases (17 files), there was no change in the TD, and for 12.68% of the cases (13 files), there was a deterioration in the value. The worsening recorded corresponds to an increase in the TD value between commits, which fluctuates in a range from 4 to 81%. Only in the remaining 18.31% of cases (9 files) does the measure of the TD of the commit removal get an improvement compared to the previous commit. In these commits, there was a decrease in the TD value ranging between 6% and 81%. \begin{table}
\begin{tabular}{l c c c c} \hline \hline  & & \multicolumn{3}{c}{**\# of Files**} \\ \hline
**Delta** & **Log4j** & **Gerrit** & **Hadoop** & **Tomcat** \\ \hline File not found & 29 & 32 & 142 & 235 \\ \hline Unchanged & 4 & 17 & 20 & 87 \\ \hline Increased & 10 & 9 & 24 & 54 \\ \hline Decreased & 20 & 13 & 19 & 100 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Previous commit analysis vs. commit removal. Even for Hadoop, there is a high percentage of cases, 69.27% (142 files), in which it was not possible to measure the variation of the technical debt due to the absence of the file to be examined in correspondence with one of the commits to be analyzed. However, for 9.27% of the cases (20 files), there was no change in the TD, in connection with the commit removal, and for 9.76% of the cases (19 files), there was a worsening of the value. In fact, there was an increase in the value of TD which varies between 0.9% and 197%. In fact, in several cases, the value of the TD between a commit and the next commit increased more than double. Two cases have even been identified in which the value increased by 400% and 500%, respectively from a value of 1 to 6 min, and 5 to 25 min. Only in the remaining 11.71% of cases (24 files) does the measure of the TD of the commit removal improve compared to the previous commit. In these cases, the decrease varied between 0.28% and 97%. These percentages suggest that only in a few circumstances are the changes made by maintainers to resolve the TD valid, while in most cases, the performed solutions do not lead to an effective decrease of the metrics values.