Research Article
Defect Prediction Technology of Aerospace Software Based on Deep Neural Network and Process Measurement
Table 6
Statistical results of experimental data.
| Software project | Experimental steps | Accuracy | Recall | Precision | F1-score |
| XX flight control software | A1-2 | 0.8843 | 0.7358 | 0.6814 | 0.6767 | A1-3 | 0.8256 | 0.7096 | 0.6722 | 0.6685 | A2-3 | 0.8911 | 0.7504 | 0.7264 | 0.7142 | A1-2-3 | 0.9106 | 0.7826 | 0.7581 | 0.7451 |
| XX fire control software | A1-2 | 0.9372 | 0.8025 | 0.7633 | 0.7562 | A1-3 | 0.9180 | 0.7634 | 0.7052 | 0.6882 | A2-3 | 0.9477 | 0.8175 | 0.7721 | 0.7580 | A1-2-3 | 0.9541 | 0.8260 | 0.7891 | 0.7726 |
| XX accused software | A1-2 | 0.8859 | 0.7246 | 0.6925 | 0.6827 | A1-3 | 0.8663 | 0.7044 | 0.6527 | 0.6475 | A2-3 | 0.8802 | 0.7330 | 0.6992 | 0.6833 | A1-2-3 | 0.8979 | 0.7421 | 0.7143 | 0.7007 |
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