## 4 Results
\begin{table}
\begin{tabular}{l c c} \hline \hline
**Metrics** & **Frequency** & **\%** \\ \hline HV & 54 & 32.1 \\ IGD & 17 & 10.1 \\ GD & 12 & 7.1 \\ Hypercube-based diversity metric & 10 & 6.0 \\ \(\Delta\), \(\epsilon\), S & 8 & 4.8 \\ NDS, ED & 6 & 3.6 \\ PFS, GS, C & 5 & 3.0 \\ HVR, ER, Contribution metric, CM & 3 & 1.8 \\ MS & 2 & 1.2 \\ R-HV, R2, MPFE, D, IGD+, ONVG, Norm-based, Proi, \(\rho\), \(\gamma\) & 1 & 0.6 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Units for list rank of used metrics. Figure 9: Metrics distribution in M6 group. The result is that HV has the highest frequency of 54, and is, thus, positioned in the first position in terms of the number of times used (frequency), and in percentage, this metric accounts for 32.1%. In the second position, IGD is presented, which has a frequency of 17 and accounts for 10.1% of the total. In position three and four, GD and the hypercube-based diversity metric (also called spread [S]) scored 12 and 10 in frequency and 7.1% and 6.0% in the percentage column, respectively. The renaming metrics are less than 6.0% in score; hence, they are the least used metrics in this report. In position five (\(\Delta\), \(\epsilon\), S) and six (NDS, ED), there are sets of metrics in the cells with total frequency scores of 8 and 6 and percentages of 4.8% and 3.6%, respectively. As shown in Table 3, the rest of the metrics account for less than 3.6% in scores. However, another RQ mainly concerns how the top metric evolution was based on grouping. RQ4: How do the top popular metrics (>5%) increase or decrease in the studies? To answer this question, we need to show the distribution of special metrics, particularly those used more than 5%, in order to increase our knowledge about how these metrics got increasingly popular or when they decreased in the overall studies. We made a bar chart to visualize the distribution of these metrics over the above-mentioned groups (M1 to M6). Figure 10 shows that for M1, M2, M3, and M5, the HV metric was the most used, and for the rest, it was used less than in M1 and M2. For the M4 and M5 groups, HV and IGD were comparable. In M2, IGD, the hypercube-based diversity metric, and GD appeared with higher values, respectively. Although the number of publications in the remaining sets is less than the previous ones, some of the metrics in this list also decreased in use, such as the hypercube-based diversity metric, which declined in use after its first appearance in M2, and it was not reported in M1, M5, or M6, while IGD was represented in all of the groups and GD is present in M2-M6. However, the graph shows most of the studies relied on HV in M1 and in M2 when the studies started using more than two metrics together with other metrics, such as IGD, GD, and the hypercube-based diversity metric. In all of the groups, HV was top-ranked except in M4, where GD was highest in frequency, and M6, where it was equal with IGD. It must be noted, however, that there are more studies in M1 and M2 (43 articles in total) compared to M3, M4, M5, and M6. This means most of the studies (according to M1-M6) employed one or two metrics, as shown in Figure 3 and Table 4. In short, this graph shows HV is preferred for DM when it comes to using one metric, while the rest of these metrics only become desirable when it comes to using more than one metric. Figure 10: Top metrics distribution over the study groups. RQ5: How well do the current studies in SBSE use performance metrics? In Table 4, the total 105 articles and the study groups (M0 to M6) together with their references are reported. The total number of articles in each set (as earlier mentioned) together with the total number of unique metrics employed in each set and the total frequencies of use shown in Figure 10 visually emphasize that more metrics are used in sets M2, M3, M4, M5, and M6. Thus, while the articles involved are fewer in quantity, more diverse metrics were used.