Research Article
Fine-Grained Software Defect Prediction Based on the Method-Call Sequence
Table 5
Comparison of different models.
| Project | MAE | MSE | Seml | DP-ARNN | TSASS | Seml | DP-ARNN | TSASS |
| EclEmma 2.1 | 0.084 | 0.126 | 0.070 | 0.0076 | 0.0198 | 0.0062 | HTML Unit 2008 | 0.273 | 0.321 | 0.201 | 0.0865 | 0.1237 | 0.0529 | HTML Unit 2010 | 0.088 | 0.176 | 0.063 | 0.0091 | 0.044 | 0.0062 | Jmol9 | 0.053 | 0.290 | 0.064 | 0.0041 | 0.0892 | 0.0079 | Jmol10 | 0.138 | 0.346 | 0.067 | 0.0307 | 0.1251 | 0.0295 | OmegaT3.5 | 0.148 | 0.376 | 0.093 | 0.037 | 0.1456 | 0.0544 | OmegaT3.6 | 0.102 | 0.451 | 0.072 | 0.0213 | 0.2079 | 0.0344 | Saros1.0.6 | 0.291 | 0.221 | 0.082 | 0.0952 | 0.0721 | 0.0138 | Unicore1.4 | 0.165 | 0.415 | 0.104 | 0.0324 | 0.1941 | 0.0180 | Unicore1.6 | 0.207 | 0.395 | 0.140 | 0.0536 | 0.1694 | 0.0313 | Average | 0.155 | 0.312 | 0.095 | 0.0377 | 0.1190 | 0.0254 |
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