RImp score for each version

//instruction

Program name:
version number: D*(Dstar): number of statements that need to be examined to find the fault, number of statements that need to be examined to find the fault with context, the percentage of executable statements to be examined before finding the actual faulty statement, the percentage of executable statements to be examined before finding the actual faulty statement with context deep learning: number of statements that need to be examined to find the fault, number of statements that need to be examined to find the fault with context, the percentage of executable statements to be examined before finding the actual faulty statement, the percentage of executable statements to be examined before finding the actual faulty statement with context RImp: deep learning(context)/D*:RImp score of our approach compared with Dstar // prinkTokens1:
v1: D*:151,56; 0.719048,0.266667
deep learning:2,1; 0.009524,0.00476 RImp: deep learning(context)/D*:0.7% v2: D*:3,3;0.014286,0.014286
deep learning:2,1; 0.009524,0.00476 RImp: deep learning(context)/D*:33.3% v3: D*:146,64;0.701923,0.307692
deep learning:76,30; RImp: deep learning(context)/D*:20.55% v5: D*:2,2;0.009524,0.009524
deep learning:5,1;0.02381,0.004762 RImp: deep learning(context)/D*:50%
v7: D*:3,1;0.014286,0.004762
deep learning:3,1;0.01429,0.00476 RImp: deep learning(context)/D*:33.3%

printTokens2:
v1: D*:24,6;0.107623,0.026906
deep learning:2,1;0.008969,0.004484 RImp: deep learning(context)/D*:45.83% v2: D*:1,1;0.004405,0.004405
deep learning:1,1;0.004405,0.004405 RImp: deep learning(context)/D*:100% v3: D*:4,3;0.017621,0.013216
deep learning:2,1;0.00881,0.00441 RImp: deep learning(context)/D*:25% v4: D*:29,11;0.127193,0.048246
deep learning:14,5;0.0614,0.02193 RImp: deep learning(context)/D*:17.24% v5: D*:1,1;0.004386,0.004386
deep learning:1,1;0.004386,0.004386 RImp: deep learning(context)/D*:100% v6: D*:1,1;0.004386,0.004386
deep learning:1,1;0.004386,0.004386 RImp: deep learning(context)/D*:100% v7: D*:2,1;0.008772,0.004386
deep learning:3,1;0.01316,0.004386 RImp: deep learning(context)/D*:50% v8: D*:21,8;0.092105,0.035088
deep learning:35,11;0.153509,0.04825 RImp: deep learning(context)/D*:52.38% v9: D*:11,6;0.048246,0.026316 deep learning:3,1; RImp: deep learning(context)/D*:9.09%

v10: D*:2,2;0.008772,0.008772
deep learning:3,1;0.01316,0.004386 RImp: deep learning(context)/D*:33.3%

schedule1:
v2: D*:11,3;0.072848,0.019868
deep learning:8,4;0.05298,0.02649 RImp: deep learning(context)/D*:36.4% v3: D*:24,7;0.158940,0.046358
deep learning:22,5;0.145695,0.03311 RImp: deep learning(context)/D*:20.83% v4: D*:123,67;0.814570,0.443709
deep learning:29,16;0.19205,0.10596 RImp: deep learning(context)/D*:13.01% v5: D*:101,38;0.673333,0.253333
deep learning:87,37;0.58,0.2467 RImp: deep learning(context)/D*:36.6% v6: D*:75,22;0.496689,0.145695
deep learning:41,13;0.2715,0.08609 RImp: deep learning(context)/D*:17.3% v7: D*:20,9;0.130719,0.058824
deep learning:39,17 RImp: deep learning(context)/D*:85% v8: D*:12,9;0.080000,0.060000
deep learning:39,17;0.26,0.1133 RImp: deep learning(context)/D*:141.7% v9: D*:60,35;0.397351,0.231788
deep learning:92,66;0.6093,0.4371 RImp: deep learning(context)/D*:110%

schedule2:
v1: D*:13,5;0.085526,0.032895
deep learning:11,7;0.07237,0.04605 RImp: deep learning(context)/D*:53.85% v3: D*:87,53;0.572368,0.348684
deep learning:85,37;0.5592,0.2434 RImp: deep learning(context)/D*:42.5% v5: D*:93,15;0.603896,0.097403
deep learning:79,12;0.5097,0.0774 RImp: deep learning(context)/D*:12.9% v6: D*:18,7;0.117647,0.045752
deep learning:37,11;0.24183,0.07190 RImp: deep learning(context)/D*:61.1% v7: D*:86,51;0.562092,0.333333
deep learning:79,45;0.5163,0.2941 RImp: deep learning(context)/D*:52.3% v8: D*:37,19;0.243421,0.125000
deep learning:25,10;0.1645,0.06579 RImp: deep learning(context)/D*:27.03% v10: D*:73,41;0.480263,0.269737
deep learning:61,29;0.4013,0.1908 RImp: deep learning(context)/D*:39.7%

Tot_info:
v1: D*:3_GP19:1,1;0.006579,0.006579
deep learning:1,1;0.006579,0.006579 RImp: deep learning(context)/D*:100% v2: D*:84,24;0.549020,0.156863
deep learning:27,5;0.176471,0.032680 RImp: deep learning(context)/D*:6.0% v3: D*:17,7;0.111111,0.045752
deep learning:16,4;0.104575,0.026144 RImp: deep learning(context)/D*:23.5% v5: D*:38,10;0.248366,0.065359
deep learning:31,8;0.202614,0.052288 RImp: deep learning(context)/D*:21.1% v6: D*:41,16;0.267974,0.104575
deep learning:8,3;0.052288,0.019608 RImp: deep learning(context)/D*:7.3% v7: D*:3_GP19:11,3;0.071895,0.019608
deep learning:47,14;0.307190,0.091503 RImp: deep learning(context)/D*:127.3% v8: D*:5,5;0.032680,0.032680
deep learning:3,3;0.019608,0.019608 RImp: deep learning(context)/D*:60% v9: D*:36,1;0.235294,0.006536
deep learning:26,17;0.169935,0.111111 RImp: deep learning(context)/D*:47.2% v13: D*:19,8;0.124183,0.052288
deep learning:25,6;0.163399,0.039216 RImp: deep learning(context)/D*:31.6% v15: D*:4,4;0.026144,0.026144
deep learning:3,2;0.019608,0.013072 RImp: deep learning(context)/D*:50% v16: D*:53,52;0.346405,0.339869
deep learning:31,21;0.202614,0.137255 RImp: deep learning(context)/D*:39.6% v17: D*:8,8;0.052288,0.052288
deep learning:46,32;0.300654,0.209150 RImp: deep learning(context)/D*:400% v18: D*:24,5;0.156863,0.032680
deep learning:32,12;0.209150,0.078431 RImp: deep learning(context)/D*:50% v20: D*:19,10;0.124183,0.065359
deep learning:17,9;0.111111,0.058824 RImp: deep learning(context)/D*:47.4% v21: D*:102,74;0.666667,0.483660
deep learning:108,63;0.705882,0.411765 RImp: deep learning(context)/D*:61.8% v22: D*:14,9;0.091503,0.058824
deep learning:15,9;0.098039,0.058824 RImp: deep learning(context)/D*:64.3% v23: D*:3,3;0.019608,0.019608
deep learning:5,3;0.032680,0.019608 RImp: deep learning(context)/D*:100%

Jtcas
v1: D*:3,2;0.034483,0.022989
deep learning:3,2;0.034483,0.022989 RImp: deep learning(context)/D*:66.7% v2: D*:1,1;0.011494,0.011494
deep learning:1,1;0.011494,0.011494 RImp: deep learning(context)/D*:100% v3: D*:26,14;0.298851,0.160920
deep learning:25,13;0.287356,0.149425 RImp: deep learning(context)/D*:50% v5: D*:18,14;0.206897,0.160920
deep learning:14,10;0.160920,0.114943 RImp: deep learning(context)/D*:55.6% v6: D*:7,7;0.080460,0.080460
deep learning:28,17;0.321839,0.195402 RImp: deep learning(context)/D*:242.9% v9: D*:14,13;0.160920,0.149425
deep learning:9,6;0.103448,0.068966 RImp: deep learning(context)/D*:42.9% v11: D*:22,14;0.252874,0.160920
deep learning:2,2;0.022989,0.022989 RImp: deep learning(context)/D*:9.1% v12: D*:14,14;0.160920,0.160920
deep learning:9,9;0.103448,0.103448 RImp: deep learning(context)/D*:64.3% v21: D*:11,10;0.126437,0.114943
deep learning:6,6;0.068966,0.068966 RImp: deep learning(context)/D*:54.5% v22: D*:13,13;0.149425,0.149425
deep learning:9,4;0.103448,0.045977 RImp: deep learning(context)/D*:30.8% v23: D*:15,14;0.172414,0.160920
deep learning:15,7;0.172414,0.080460 RImp: deep learning(context)/D*:46.7% v25: D*:5,5;0.057471,0.057471
deep learning:13,9;0.149425,0.103448 RImp: deep learning(context)/D*:180% v26: D*:21,18;0.241379,0.206897
deep learning:11,8;0.126437,0.091954 RImp: deep learning(context)/D*:38.1% v31: D*:8,8;0.091954,0.091954
deep learning:5,5;0.057471,0.057471 RImp: deep learning(context)/D*:62.5%

nanoxml_v1:
f1:
D*:164,99;
deep learning: 165,66; RImp: deep learning(context)/D*:40.2% f2: D*:463,297;
deep learning:396,165; RImp: deep learning(context)/D*:35.6% f3: D*:462,297;
deep learning:429,198; RImp: deep learning(context)/D*:42.9%

nanoxml_v2:
f1:
D*:128,96;
deep learning: 160,95; RImp: deep learning(context)/D*:74.2% f2: D*:160,64;
deep learning:128,98; RImp: deep learning(context)/D*:61.3% f3: D*:448,288;
deep learning:512,223; RImp: deep learning(context)/D*:49.8%

nanoxml_v3:
f1:
D*:2210,130;
deep learning: 780,260; RImp: deep learning(context)/D*:11.8% f2: D*:130,130;
deep learning:390,120; RImp: deep learning(context)/D*:92.3% f3: D*:7800,2340;
deep learning:4940,1440; RImp: deep learning(context)/D*:18.5% f4:
D*:1040,390;
deep learning: 1430,130; RImp: deep learning(context)/D*:12.5% f5:
D*:3120,2860;
deep learning:1560,260; RImp: deep learning(context)/D*:8.3% f6: D*:520,390;
deep learning:130,127; RImp: deep learning(context)/D*:24.4% f7: D*:1820,1170;
deep learning:2210,653; RImp: deep learning(context)/D*:35.9%

nanoxml_v5:
f1: D*:2584,760;
deep learning:1976,912; RImp: deep learning(context)/D*:35.3% f2: D*:4255,2128;
deep learning:2736,1064; RImp: deep learning(context)/D*:25.01% f3: D*:609,456;
deep learning:608,456; RImp: deep learning(context)/D*:74.9% f4: D*:1976,1216;
deep learning:1368,608; RImp: deep learning(context)/D*:30.8% f5: D*:2128,304;
deep learning:1672,304; RImp: deep learning(context)/D*:14.3%