## 5 Experimental Results
### RQ2. How Effective Is the Proposed Approach in Test Case Prioritization in Testing CAD Software?
\begin{table}
\begin{tabular}{l l l l l l l l} \hline
**Test Set** & **Ranking Model** & **Precision** & **Recall** & **F-Score** & **Accuracy** & **Time (ms)** & **Memory (MB)** \\ \hline \multirow{6}{*}{math} & CART & 87.31\% & 88.54\% & 87.93\% & 87.03\% & 37.49 & **200.99** \\  & RF & 91.14\% & 81.62\% & 86.12\% & 85.97\% & 30.23 & 246.34 \\  & SVM & 53.33\% & 100\% & 69.56\% & 53.33\% & 29.17 & 294.53 \\  & BN & 22.86\% & 0.51\% & 0.99\% & 46.03\% & **27.96** & 251.96 \\  & CNN & 53.33\% & 100\% & 69.56\% & 53.33\% & 41.85 & 358.33 \\  & RNN & 53.33\% & 100\% & 69.59\% & 53.33\% & 20.01 & 275.79 \\ \hline \multirow{6}{*}{object} & CART & 88.12\% & 84.50\% & 86.28\% & 85.66\% & 126.66 & 710.58 \\  & RF & 89.45\% & 79.09\% & 83.96\% & 83.88\% & 202.42 & 826.45 \\  & SVM & N/A & 0\% & N/A & 46.67\% & **117.87** & **558.3** \\  & BN & 64.01\% & 21.82\% & 32.55\% & 51.76\% & **151.64** & 696.19 \\  & CNN & N/A & 0\% & N/A & 46.67\% & 206.12 & 897.85 \\  & RNN & N/A & 0\% & N/A & 46.67\% & 285.83 & 768.95 \\ \hline \multirow{6}{*}{procedural} & CART & 92.89\% & 83.25\% & 87.80\% & 87.67\% & 40.91 & 218.17 \\  & RF & 92.43\% & 80.22\% & 85.89\% & 85.95\% & **35.94** & 280.97 \\  & SVM & 53.33\% & 100\% & 69.56\% & 53.33\% & 60.62 & 219.94 \\  & BN & 22.58\% & 0.5\% & 0.97\% & 46.03\% & 63.37 & 288.06 \\  & CNN & 53.33\% & 100\% & 69.56\% & 53.33\% & 46.21 & 338.44 \\  & RNN & 53.33\% & 100\% & 69.56\% & 53.33\% & 74.97 & **193.84** \\ \hline \multirow{6}{*}{Fold 1} & CART & 29.78\% & 43.56\% & 35.38\% & 43.71\% & 65.31 & 273.88 \\  & RF & 50.99\% & 92\% & 65.61\% & 65.88\% & 75.31 & 335.16 \\  & SVM & 35.38\% & 100\% & 52.26\% & 35.38\% & 72.88 & 301.46 \\  & BN & 65.04\% & 71.11\% & 67.94\% & 76.26\% & **30.17** & **189.84** \\  & CNN & 35.38\% & 100\% & 52.26\% & 35.38\% & 41.64 & 257.77 \\  & RNN & 35.38\% & 100\% & 52.26\% & 35.38\% & 36.03 & 331.65 \\ \hline \multirow{6}{*}{Fold 2} & CART & 42.06\% & 79.67\% & 55.06\% & 74.84\% & 78.34 & 320.61 \\  & RF & 47.27\% & 63.41\% & 54.17\% & 79.25\% & 62.81 & **169.62** \\  & SVM & 19.34\% & 100\% & 32.41\% & 19.34\% & 69.69 & 284.75 \\  & BN & 16.92\% & 17.89\% & 17.39\% & 67.19\% & **35.03** & 178.8 \\  & CNN & 19.34\% & 100\% & 32.41\% & 19.34\% & 75.26 & 249.2 \\  & RNN & 19.34\% & 100\% & 32.41\% & 19.34\% & 41.59 & 226.92 \\ \hline \multirow{6}{*}{Fold 3} & CART & 55.56\% & 60.98\% & 58.14\% & 60.38\% & 77.24 & 275.33 \\  & RF & 59.75\% & 84.32\% & 69.94\% & 67.37\% & 38.26 & 338.93 \\ \cline{1-1}  & SVM & 45.13\% & 100\% & 62.19\% & 45.13\% & **35.02** & **175.69** \\ \cline{1-1}  & BN & 20.97\% & 18.19\% & 19.44\% & 32.23\% & 72.33 & 389.09 \\ \cline{1-1}  & CNN & 45.13\% & 100\% & 62.19\% & 45.13\% & 72.9 & 336.95 \\ \cline{1-1}  & RNN & 45.13\% & 100\% & 62.19\% & 45.13\% & 59.32 & 189.21 \\ \hline \multirow{6}{*}{Fold 4} & CART & 41.04\% & 21.59\% & 28.29\% & 30.66\% & 48.16 & 278.7 \\ \cline{1-1}  & RF & 58.96\% & 44.91\% & 50.99\% & 45.28\% & 51.04 & 282.38 \\ \cline{1-1}  & SVM & N/A & 0 & N/A & 36.64\% & **32.36** & 380.15 \\ \cline{1-1}  & BN & 7.27\% & 2.98\% & 4.23\% & 14.47\% & 60.11 & 226.24 \\ \cline{1-1}  & CNN & N/A & 0 & N/A & 36.64\% & 35.28 & **185.58** \\ \cline{1-1}  & RNN & N/A & 0 & N/A & 36.64\% & 63.32 & 217.7 \\ \hline \multirow{6}{*}{Fold 5} & CART & 73.53\% & 38.99\% & 50.96\% & 39.84\% & 42.56 & **221.22** \\ \cline{1-1}  & RF & 87\% & 80.9\% & 83.84\% & 759\% & **32.09** & 248.61 \\ \cline{1-1}  & SVM & 80.63\% & 100\% & 89.27\% & 80.63\% & 70.12 & 249.8 \\ \cline{1-1}  & BN & 53.06\% & 15.2\% & 23.64\% & 21.25\% & 44.91 & 353.38 \\ \cline{1-1}  & CNN & 80.63\% & 100\% & 89.27\% & 80.63\% & 33.8 & 294.55 \\ \cline{1-1}  & RNN & 80.63\% & 100\% & 89.27\% & 80.63\% & 65.31 & 253.19 \\ \hline \end{tabular}
\end{table} 
Table 4: Results of six ranking models under six evaluation metrics.