Research Article
Fine-Grained Software Defect Prediction Based on the Method-Call Sequence
Table 6
Comparison of different methods.
| Project | MAE | MSE | Seml | DP-ARNN | TSASS | Seml | DP-ARNN | TSASS |
| EclEmma2.1 | 0.118 | 0.053 | 0.070 | 0.0417 | 0.0407 | 0.0062 | HTML Unit 2008 | 0.271 | 0.298 | 0.201 | 0.0806 | 0.0955 | 0.0529 | HTML Unit 2010 | 0.156 | 0.131 | 0.063 | 0.0380 | 0.0393 | 0.0062 | Jmol9 | 0.122 | 0.116 | 0.064 | 0.0390 | 0.0402 | 0.0079 | Jmol10 | 0.180 | 0.109 | 0.067 | 0.0515 | 0.0201 | 0.0295 | OmegaT3.5 | 0.109 | 0.121 | 0.093 | 0.0198 | 0.0249 | 0.0544 | OmegaT3.6 | 0.242 | 0.189 | 0.072 | 0.0631 | 0.0739 | 0.0344 | Saros1.0.6 | 0.174 | 0.371 | 0.082 | 0.0724 | 0.1436 | 0.0138 | Unicore1.4 | 0.206 | 0.219 | 0.104 | 0.0576 | 0.0622 | 0.0180 | Unicore1.6 | 0.172 | 0.168 | 0.140 | 0.0338 | 0.0323 | 0.0313 | Average | 0.175 | 0.177 | 0.095 | 0.0497 | 0.0572 | 0.0254 |
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