## 5 Results and Data Analysis
### RQ1: Maintainability Measurement in a Software System
\begin{table}
\begin{tabular}{l l l l l l l} \hline \hline  & \(\textsubscript{MI}_{\textit{orig.}}\) & \(\textsubscript{MI}_{\textit{orig.(CM)}}\) & \(\textsubscript{MI}_{\textit{impr.}}\) & \(\textsubscript{MI}_{\textit{impror.(CM)}}\) & \(\textsubscript{MI}_{\textit{LOC}}\) & \(\textsubscript{MI}_{\textit{IH}}\) & \(\textsubscript{MI}_{\textit{IH}(\textit{CM})}\) \\ \hline Avg. & 66.66 & 112.41 & 60.90 & 106.64 & 59.23 & 66.37 & 112.11 \\
95\% CI & [62.64, 70.69] & [108.35, 116.47] & [56.73, 65.07] & [102.48, 110.8] & [54.87, 63.59] & [62.13, 70.61] & [107.87, 116.36] \\ Med. & 67.74 & 111.37 & 61.04 & 105 & 59.98 & 66.74 & 112.15 \\ Std. & 13.39 & 13.51 & 13.88 & 13.84 & 14.51 & 14.13 & 14.14 \\ Min. & 44.29 & 82.70 & 36.90 & 78.44 & 33.45 & 42.54 & 83.70 \\ Max. & 94.74 & 136.82 & 89.78 & 131.86 & 88.23 & 96.71 & 138.78 \\ Skew. & 0.06 & 0.03 & 0.06 & 0.04 & \(-\)0.01 & 0.10 & 0.08 \\ Kurt. & \(-\)1.00 & \(-\)0.69 & \(-\)0.93 & \(-\)0.72 & \(-\)0.97 & \(-\)0.90 & \(-\)0.68 \\ SW & \(\text{W}=0.96\), & \(\text{W}=0.98\), & \(\text{W}=0.97\), & \(\text{W}=0.97\), & \(\text{W}=0.97\), & \(\text{W}=0.96\), & \(\text{W}=0.97\), \\  & \(\text{p}=0.147\) & \(\text{p}=0.461\) & \(\text{p}=0.207\) & \(\text{p}=0.389\) & \(\text{p}=0.256\) & \(\text{p}=0.165\) & \(\text{p}=0.352\) \\ \hline \hline \end{tabular} Avg. = average, CI = confidence interval, Med. = median, Std. = standard deviation, Min. = minimum, Max. = maximum, Skew = skewness, Kurt. = kurtosis, SW = Shapiro-Wilk Test.  
\end{table} 
Table 9: Descriptive statistics and normality test of Index variant values. Figure 2: Dot plot of Index variant values for each subject software system. and \(MI_{JH}\) are inconsistent, as some subject software systems have higher maintainability based on \(MI_{orig. }\) (e.g., in the case of \(S1\)), while others have higher maintainability based on \(MI_{JH}\) (e.g., in the case of \(S4\)). The Index variants without comment parts have smaller differences from Index variants without comment parts compared to Index variants with comment parts. For instance, the mean value of the absolute difference between \(MI_{orig. }\) and \(MI_{impr. }\), \(MI_{LOC}\), and \(MI_{JH}\) is 5.77, 7.43, and 1.50, respectively, while the mean value of the absolute difference between \(MI_{orig. }\) and \(MI_{orig. (CM)}\), \(MI_{impr. (CM)}\), and \(MI_{JH(CM)}\) is 45.74, 39.98, and 45.45, respectively. Similarly, it can be observed that the Index variants with comment parts have smaller differences from Index variants with comment parts compared to Index variants without comment parts. For instance, the mean value of the absolute difference between \(MI_{orig. (CM)}\) and \(MI_{impr. (CM)}\) and \(MI_{JH(CM)}\) is 5.77 and 1.50, respectively, while the mean value of the absolute difference between \(MI_{orig. (CM)}\) and \(MI_{orig. }\), \(MI_{impr. }\), \(MI_{LOC}\), and \(MI_{JH}\) is 45.74, 51.51, 53.18, and 46.04, respectively. Figure 3: Boxplots of the pairwise differences between Index variant values. The differences between the values of Index variants are evaluated in Table 10 using inferential statistics. Note that the Shapiro-Wilk Test was used to verify normality assumptions, and the appropriate test was then used, either the Paired Samples \(t\)-Test, when the normality assumptions were met, or the Wilcoxon Signed-Rank Test, when the normality assumptions were not met. To accompany the former, the average difference with the standard error and \(d\) effect size are reported in the table, while to accompany the latter, the median difference and \(r_{c}\) effect size are reported. All differences were found to be statistically significant, except for the differences between \(Ml_{orig. }\) and \(Ml_{JH}\) and between \(Ml_{orig. (CM)}\) and \(Ml_{JH(CM)}\). In Figure 4, the boxplots of the Index variants with statistical significance annotations are depicted (only non-significant pairs are annotated). The boxplots of the non-significant pairs show a negligible difference, while the rest of the boxplots visibly differ.